Multimodal task execution and text editing for a wearable system

ABSTRACT

Examples of wearable systems and methods can use multiple inputs (e.g., gesture, head pose, eye gaze, voice, and/or environmental factors (e.g., location)) to determine a command that should be executed and objects in the three-dimensional (3D) environment that should be operated on. The multiple inputs can also be used by the wearable system to permit a user to interact with text, such as, e.g., composing, selecting, or editing text.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. patent application Ser. No.16/984,926, filed on Aug. 8, 2020, entitled “MULTIMODAL TASK EXECUTIONAND TEXT EDITING FOR A WEARABLE SYSTEM,” which is a continuationapplication of U.S. patent application Ser. No. 15/955,204, filed onApr. 17, 2018, entitled “MULTIMODAL TASK EXECUTION AND TEXT EDITING FORA WEARABLE SYSTEM,” which claims the benefit of priority under 35 U.S.C.§ 119(e) to U.S. Provisional Application No. 62/487,364, filed on Apr.19, 2017, entitled “MULTI-MODAL CONTEXTUAL TASK EXECUTION FOR AUGMENTEDREALITY,” and U.S. Provisional Application No. 62/609,647, filed on Dec.22, 2017, entitled “MULTI-MODAL TEXT COMPOSITION AND EDITING FORAUGMENTED REALITY,” the disclosures of which are hereby incorporated byreference herein in their entireties.

FIELD

The present disclosure relates to virtual reality and augmented realityimaging and visualization systems and more particularly to interactingwith virtual objects or text in a three-dimensional (3D) environmentusing a combination of user inputs.

BACKGROUND

Modern computing and display technologies have facilitated thedevelopment of systems for so called “virtual reality”, “augmentedreality”, or “mixed reality” experiences, wherein digitally reproducedimages or portions thereof are presented to a user in a manner whereinthey seem to be, or may be perceived as, real. A virtual reality, or“VR”, scenario typically involves presentation of digital or virtualimage information without transparency to other actual real-world visualinput; an augmented reality, or “AR”, scenario typically involvespresentation of digital or virtual image information as an augmentationto visualization of the actual world around the user; a mixed reality,or “MR”, related to merging real and virtual worlds to produce newenvironments where physical and virtual objects co-exist and interact inreal time. As it turns out, the human visual perception system is verycomplex, and producing a VR, AR, or MR technology that facilitates acomfortable, natural-feeling, rich presentation of virtual imageelements amongst other virtual or real-world imagery elements ischallenging. Systems and methods disclosed herein address variouschallenges related to VR, AR and MR technology.

SUMMARY

Examples of wearable systems and methods described herein can usemultiple inputs (e.g., gesture, head pose, eye gaze, voice, orenvironmental factors (e.g., location)) to determine a command thatshould be executed and objects in the three dimensional (3D) environmentthat should be operated on. The multiple inputs can also be used by thewearable device to permit a user to interact with text, such as, e.g.,composing, selecting, or editing text.

For example, a wearable display device can be configured to parsemultimodal inputs for execution of a task. The wearable device can use acombination of multiple inputs such as head pose, eye gaze, handgestures, voice commands, environmental factors (e.g., the user'slocation or the objects around the users) to determine which virtualobject in the user's environment the wearable device will operate on,what type of operations the wearable device can execute on the virtualobject, and how the wearable device executes the operations.

As another example, a wearable device can be configured to parsemultimodal inputs for interacting with text. The wearable device can usea combination of multiple inputs such as voice inputs, eye gaze, handgestures, and totem inputs to compose (e.g., input) and edit text. Thewearable device may enable a user to utilize a first mode of input(e.g., voice inputs) to dictate text to the system, utilize a second anddifferent mode of input (e.g., eye gaze input or body gestures) toselect parts of the text for editing, and utilize the first mode, thesecond mode, yet another mode, or a combination of modes thereof to editselected text.

Details of one or more implementations of the subject matter describedin this specification are set forth in the accompanying drawings and thedescription below. Other features, aspects, and advantages will becomeapparent from the description, the drawings, and the claims. Neitherthis summary nor the following detailed description purports to defineor limit the scope of the inventive subject matter.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 depicts an illustration of a mixed reality scenario with certainvirtual reality objects, and certain physical objects viewed by aperson.

FIG. 2 schematically illustrates an example of a wearable system.

FIG. 3 schematically illustrates aspects of an approach for simulatingthree-dimensional imagery using multiple depth planes.

FIG. 4 schematically illustrates an example of a waveguide stack foroutputting image information to a user.

FIG. 5 shows example exit beams that may be outputted by a waveguide.

FIG. 6 is a schematic diagram showing an optical system including awaveguide apparatus, an optical coupler subsystem to optically couplelight to or from the waveguide apparatus, and a control subsystem, usedin the generation of a multi-focal volumetric display, image, or lightfield.

FIG. 7 is a block diagram of an example of a wearable system.

FIG. 8 is a process flow diagram of an example of a method of renderingvirtual content in relation to recognized objects.

FIG. 9 is a block diagram of another example of a wearable system.

FIG. 10 is a process flow diagram of an example of a method fordetermining user input to a wearable system.

FIG. 11 is a process flow diagram of an example of a method forinteracting with a virtual user interface.

FIG. 12A schematically illustrates an example of a field of regard(FOR), a field of view (FOV) of a world camera, a field of view of auser, and a field of fixation of a user.

FIG. 12B schematically illustrates an example of virtual objects in auser's field of view and virtual objects in a field of regard.

FIG. 13 illustrates examples of interacting with a virtual object usingone mode of user input.

FIG. 14 illustrates examples of selecting a virtual object using acombination of user input modes.

FIG. 15 illustrates an example of interacting with a virtual objectusing a combination of direct user inputs.

FIG. 16 illustrates an example computing environment for aggregatinginput modes.

FIG. 17A illustrates an example of identifying a target virtual objectusing a lattice tree analysis.

FIG. 17B illustrates an example of determining a target user interfaceoperation based on multimodal inputs.

FIG. 17C illustrates an example of aggregating confidence scoresassociated with input modes for a virtual object.

FIGS. 18A and 18B illustrate examples of calculating confidence scoresfor objects within a user's FOV.

FIGS. 19A and 19B illustrate an example of interacting with a physicalenvironment using multimodal inputs.

FIG. 20 illustrates an example of automatically resizing a virtualobject based on multimodal inputs.

FIG. 21 illustrates an example of identifying a target virtual objectbased on objects' locations.

FIGS. 22A and 22B illustrate another example of interacting with auser's environment based on a combination of direct and indirect inputs.

FIG. 23 illustrates an example process of interacting with a virtualobject using multimodal inputs.

FIG. 24 illustrates an example of setting direct input modes associatedwith a user interaction.

FIG. 25 illustrates an example of user experience with multimodal input.

FIG. 26 illustrates an example user interface with a variety ofbookmarked applications.

FIG. 27 illustrates an example user interface when a search command isissued.

FIGS. 28A-28F illustrate an example user experience of composing andediting a text based on a combination of voice and gaze inputs.

FIG. 29 illustrates an example of selecting a word based on an inputfrom a user input device and gaze.

FIG. 30 illustrates an example of selecting a word for editing based ona combination of voice and gaze inputs.

FIG. 31 illustrates an example of selecting a word for editing based ona combination of gaze and gesture inputs.

FIG. 32 illustrates an example of replacing a word based on acombination of eye gaze and voice inputs.

FIG. 33 illustrates an example of changing a word based on a combinationof voice and gaze inputs.

FIG. 34 illustrates an example of editing a selected word using avirtual keyboard.

FIG. 35 illustrates an example user interface that displays possibleactions to apply to a selected word.

FIG. 36 illustrates examples of interacting with a phrase usingmultimodal inputs.

FIGS. 37A and 37B illustrate additional examples of using multimodalinputs to interact with a text.

FIG. 38 is a process flow diagram of an example method of using multiplemodes of user input to interact with a text.

Throughout the drawings, reference numbers may be re-used to indicatecorrespondence between referenced elements. The drawings are provided toillustrate example embodiments described herein and are not intended tolimit the scope of the disclosure.

DETAILED DESCRIPTION Overview

Modern computing systems can possess a variety of user interactions. Awearable device can present an interactive VR/AR/MR environment whichcan comprise data elements that may be interacted with by a user througha variety of inputs. Modern computing systems are typically engineeredto generate a given output based on a single direct input. For example,a keyboard will relay text input as received from finger strokes of auser. A voice recognition application can create an executable datastring based on a user's voice as a direct input. A computer mouse canguide a cursor in response to a user's direct manipulation (e.g., theuser's hand movement or gesture). The various ways a user can interactwith the system are sometimes referred to herein as modes of userinputs. For example, a user input via a mouse or keyboard is ahand-gesture-based mode of interaction (because the fingers of a handpress keys on a keyboard or the hand moves a mouse).

However, conventional input techniques, such as keyboard, user inputdevice, gestures, etc., in a data rich and dynamic interactionenvironment (e.g., the AR/VR/MR environment) may require a high degreeof specificity to accomplish a desired task. Otherwise, in the absenceof precise inputs, the computing systems may suffer a high error rateand may cause incorrect computer operations to be performed. Forexample, when a user intends a move an object in a 3D space using atouchpad, the computing systems may not be able to correctly interpret amove command if the user does not specify a destination or specify theobject using the touchpad. As another example, inputting a string oftext using a virtual keyboard (e.g., as manipulated with a user inputdevice or by gesture) as the only mode of input can be slow andphysically fatiguing, because it requires prolonged fine motor controlto type the described keys in mid-air or on a physical surface (e.g., adesk) where the virtual keyboard is rendered.

To reduce the degree of specificity required in an input command and toreduce error rate associated with an imprecise command, the wearablesystem described herein can be programmed to apply multimodal inputs forexecution of an interaction event, such as e.g., a task for selecting,moving, resizing or targeting a virtual object. The interaction eventcan include causing an application associated with the virtual object toexecute (e.g., if the target object is a media player, the interactionevent can comprise causing the media player to play a song or video).Selecting the target virtual object can comprise executing anapplication associated with the target virtual object. Multimodal inputsutilize two or more types of input (or inputs from multiple inputchannels) to generate the command for execution of a task. As will befurther explained herein, input modes can include, but are not limitedto, hand gestures, head pose, eye gaze, voice commands, environmentalinputs (e.g., position of the user or objects in the user'senvironment), etc. For example, when a user says “move that there”, thewearable system can use head pose, eye gaze, hand gestures, along withother environmental factors (e.g. the user's location or the location ofobjects around the user), in combination with the voice command todetermine which object should be moved (e.g., which object is “that”)and which destination is intended (e.g., “there”) in response to thesemultimodal inputs.

As will further be described herein, the techniques for multimodalinputs are not merely an aggregation of multiple user input modes.Rather, the wearable system employing such techniques can advantageouslysupport the added depth dimension in 3D (as compared to traditional 2Dinteractions) provided in the wearable system. The added dimension notonly enables additional types of user interactions (e.g., rotations, ormovements along the additional axis in a Cartesian coordinate system),but also requires a high degree of precision of a user input to providethe correct outcome. The user inputs for interacting with virtualobjects, however, are not always accurate due to a user's limitations onmotor controls. Although traditional input techniques can calibrate andadjust to the inaccuracies of a user's motor controls in 2D space, suchinaccuracies are magnified in 3D space due to the added dimension.Traditional input methods, such as keyboard input, however, are not wellsuited for adjusting such inaccuracies in 3D space. Accordingly, onebenefit provided by the multimodal input techniques (among otherbenefits) is to adapt traditional input methods into fluid and moreaccurate interactions with objects in the 3D space.

In addition, advantageously, in some embodiments, the techniquesdescribed herein can reduce the hardware requirements and cost of thewearable system. For example, a wearable device may use low resolutioneye-tracking cameras in connection with the voice command to execute atask rather than employ a high resolution eye-tracking camera (which canbe expensive and complex to utilize) by itself to determine the taskbased on the multimodal combination of the user's eye gaze direction andvoice command. In this example, the use of the user's voice command cancompensate for the lower resolution at which the eye-tracking isperformed. Accordingly, multimodal combinations of a plurality of userinput modes can provide for lower cost, less complex, and more robustuser interactions with AR/VR/MR devices than the use of a single inputmode. Additional benefits and examples of techniques related tomultimodal inputs for interacting with virtual objects are furtherdescribed with reference to FIGS. 13-27.

The wearable system can also advantageously support interactions with atext using multimodal input controls. As previously noted, conventionalinput techniques, employed individually, are problematic in an AR/VR/MRenvironment. For example, an input with a user input device, gesture, oran eye gaze (e.g., via interaction with a virtual keyboard) requiresfine motor control, and thus can be slow and fatiguing. A virtualkeyboard with character insertions manipulated by gaze has a relativelylow ceiling with regard to the speed of text input (e.g., estimated atabout 10-35 words per minutes). Spoken input, although very fast (e.g.,estimated at about 100-150 words per minutes) can be prone to error dueto misrecognition or artifacts of disfluency (e.g., for various reasonssuch as poor enunciation, environmental noise, use of homonyms, use ofidiosyncratic or simply unfamiliar vocabulary, etc.). Text editing(e.g., correcting errors revising for other reasons) using a single modeinput can be particularly challenging because of the difficulty ofmaking selections and substitutions absent a very accurate set ofcommands.

Advantageously, in some embodiments, the wearable system describedherein can facilitate text input and editing in various systemsincluding mixed reality systems by combining available input methods,and enabling users to utilize a combination of user inputs to accomplishefficient interactions with texts (such as, e.g., composing, selectingand editing text). As an example, speech may be used as the primarymethod of inputting text into the system. Speech can be combined witheye gaze as a method of selecting text for editing and revision andmanipulation of graphical user interface elements in general. Thewearable system can also enable execution of any given task (e.g.,replacing a particular text string with a different string) using acombination of interaction modalities (e.g., selection using gaze andreplacement using speech).

Accordingly, as will further be described with reference to FIGS. 28A-38the wearable system provides users with the ability to compose textualmessages using speech, and edit such messages using gaze or another typeof input different from speech (e.g., body gestures). The wearablesystem may be configured to receive audio inputs, such as, e.g., aspeech input (e.g., utterances) from a user, or a sound from anenvironment, generate a transcription of the speech input (e.g., usingautomated speech recognition (ASR)), present the user with a textualrepresentation (e.g., textual characters displayed in mixed reality) ofthe generated transcription, receive another type of input from the user(e.g., gaze input, gesture input, etc.), and select and edit a portionof the transcription based on the other type of input received from theuser.

By combining user input modalities this way, the text composition andediting process may be faster and more intuitive, because speech inputcan be more effective than gaze input for composition (e.g., gaze typingcan be fatiguing) and gaze input (or gesture input) may be moreeffective than speech input for editing (e.g., selecting or changingtranscribed messages using speech can be prone to error).

Examples of 3D Display of a Wearable System

A wearable system (also referred to herein as an augmented reality (AR)system) can be configured to present 2D or 3D virtual images to a user.The images may be still images, frames of a video, or a video, incombination or the like. The wearable system can include a wearabledevice that can present VR, AR, or MR content in an environment, aloneor in combination, for user interaction. The wearable device can be ahead-mounted device (HMD) which can includes a head-mounted display. Insome situations, the wearable device is referred to interchangeably asan AR device (ARD).

FIG. 1 depicts an illustration of a mixed reality scenario with certainvirtual reality objects, and certain physical objects viewed by aperson. In FIG. 1, an MR scene 100 is depicted wherein a user of an MRtechnology sees a real-world park-like setting 110 featuring people,trees, buildings in the background, and a concrete platform 120. Inaddition to these items, the user of the MR technology also perceivesthat he “sees” a robot statue 130 standing upon the real-world platform120, and a cartoon-like avatar character 140 flying by which seems to bea personification of a bumble bee, even though these elements do notexist in the real world.

In order for the 3D display to produce a true sensation of depth, andmore specifically, a simulated sensation of surface depth, it may bedesirable for each point in the display's visual field to generate anaccommodative response corresponding to its virtual depth. If theaccommodative response to a display point does not correspond to thevirtual depth of that point, as determined by the binocular depth cuesof convergence and stereopsis, the human eye may experience anaccommodation conflict, resulting in unstable imaging, harmful eyestrain, headaches, and, in the absence of accommodation information,almost a complete lack of surface depth.

VR, AR, and MR experiences can be provided by display systems havingdisplays in which images corresponding to a plurality of renderingplanes are provided to a viewer. A rendering plane can correspond to adepth plane or multiple depth planes. The images may be different foreach rendering plane (e.g., provide slightly different presentations ofa scene or object) and may be separately focused by the viewer's eyes,thereby helping to provide the user with depth cues based on theaccommodation of the eye required to bring into focus different imagefeatures for the scene located on different rendering plane or based onobserving different image features on different rendering planes beingout of focus. As discussed elsewhere herein, such depth cues providecredible perceptions of depth.

FIG. 2 illustrates an example of wearable system 200. The wearablesystem 200 includes a display 220, and various mechanical and electronicmodules and systems to support the functioning of display 220. Thedisplay 220 may be coupled to a frame 230, which is wearable by a user,wearer, or viewer 210. The display 220 can be positioned in front of theeyes of the user 210. The display 220 can present AR/VR/MR content to auser. The display 220 can comprise a head mounted display (HMD) that isworn on the head of the user. In some embodiments, a speaker 240 iscoupled to the frame 230 and positioned adjacent the ear canal of theuser (in some embodiments, another speaker, not shown, is positionedadjacent the other ear canal of the user to provide for stereo/shapeablesound control). The display 220 can include an audio sensor 232 (e.g., amicrophone) for detecting an audio stream from the environment on whichto perform voice recognition.

The wearable system 200 can include an outward-facing imaging system 464(shown in FIG. 4) which observes the world in the environment around theuser. The wearable system 200 can also include an inward-facing imagingsystem 462 (shown in FIG. 4) which can track the eye movements of theuser. The inward-facing imaging system may track either one eye'smovements or both eyes' movements. The inward-facing imaging system 462may be attached to the frame 230 and may be in electrical communicationwith the processing modules 260 or 270, which may process imageinformation acquired by the inward-facing imaging system to determine,e.g., the pupil diameters or orientations of the eyes, eye movements oreye pose of the user 210.

As an example, the wearable system 200 can use the outward-facingimaging system 464 or the inward-facing imaging system 462 to acquireimages of a pose of the user. The images may be still images, frames ofa video, or a video, in combination or the like.

The display 220 can be operatively coupled 250, such as by a wired leador wireless connectivity, to a local data processing module 260 whichmay be mounted in a variety of configurations, such as fixedly attachedto the frame 230, fixedly attached to a helmet or hat worn by the user,embedded in headphones, or otherwise removably attached to the user 210(e.g., in a backpack-style configuration, in a belt-coupling styleconfiguration).

The local processing and data module 260 may comprise a hardwareprocessor, as well as digital memory, such as non-volatile memory (e.g.,flash memory), both of which may be utilized to assist in theprocessing, caching, and storage of data. The data may include data a)captured from environmental sensors (which may be, e.g., operativelycoupled to the frame 230 or otherwise attached to the user 210), audiosensors 232 (e.g., microphones); or b) acquired or processed usingremote processing module 270 or remote data repository 280, possibly forpassage to the display 220 after such processing or retrieval. The localprocessing and data module 260 may be operatively coupled bycommunication links 262 or 264, such as via wired or wirelesscommunication links, to the remote processing module 270 or remote datarepository 280 such that these remote modules are available as resourcesto the local processing and data module 260. In addition, remoteprocessing module 280 and remote data repository 280 may be operativelycoupled to each other.

In some embodiments, the remote processing module 270 may comprise oneor more processors configured to analyze and process data and/or imageinformation. In some embodiments, the remote data repository 280 maycomprise a digital data storage facility, which may be available throughthe internet or other networking configuration in a “cloud” resourceconfiguration. In some embodiments, all data is stored and allcomputations are performed in the local processing and data module,allowing fully autonomous use from a remote module.

In addition to or in alternative to the components described in FIG. 2,the wearable system 200 can include environmental sensors to detectobjects, stimuli, people, animals, locations, or other aspects of theworld around the user. The environmental sensors may include imagecapture devices (e.g., cameras, inward-facing imaging system,outward-facing imaging system, etc.), microphones, inertial measurementunits (IMUs), accelerometers, magnetometers (compasses), globalpositioning system (GPS) units, radio devices, gyroscopes, altimeters,barometers, chemical sensors, humidity sensors, temperature sensors,external microphones, light sensors (e.g., light meters), timing devices(e.g., clocks or calendars), or any combination or subcombinationthereof. In certain embodiments, an IMU may be a 9-Axis IMU which caninclude a triple-axis gyroscope, a triple-axis accelerometer, and atriple-axis magnetometer.

Environmental sensors may also include a variety of physiologicalsensors. These sensors can measure or estimate the user's physiologicalparameters such as heart rate, respiratory rate, galvanic skin response,blood pressure, encephalographic state, and so on. Environmental sensorsmay further include emissions devices configured to receive signals suchas laser, visible light, invisible wavelengths of light, or sound (e.g.,audible sound, ultrasound, or other frequencies). In some embodiments,one or more environmental sensors (e.g., cameras or light sensors) maybe configured to measure the ambient light (e.g., luminance) of theenvironment (e.g., to capture the lighting conditions of theenvironment). Physical contact sensors, such as strain gauges, curbfeelers, or the like, may also be included as environmental sensors.

The human visual system is complicated and providing a realisticperception of depth is challenging. Without being limited by theory, itis believed that viewers of an object may perceive the object as beingthree-dimensional due to a combination of vergence and accommodation.Vergence movements (e.g., rolling movements of the pupils toward or awayfrom each other to converge the lines of sight of the eyes to fixateupon an object) of the two eyes relative to each other are closelyassociated with focusing (or “accommodation”) of the lenses of the eyes.Under normal conditions, changing the focus of the lenses of the eyes,or accommodating the eyes, to change focus from one object to anotherobject at a different distance will automatically cause a matchingchange in vergence to the same distance, under a relationship known asthe “accommodation-vergence reflex.” Likewise, a change in vergence willtrigger a matching change in accommodation, under normal conditions.Display systems that provide a better match between accommodation andvergence may form more realistic and comfortable simulations ofthree-dimensional imagery.

FIG. 3 illustrates aspects of an approach for simulating athree-dimensional imagery using multiple rendering planes. Withreference to FIG. 3, objects at various distances from eyes 302 and 304on the z-axis are accommodated by the eyes 302 and 304 so that thoseobjects are in focus. The eyes 302 and 304 assume particularaccommodated states to bring into focus objects at different distancesalong the z-axis. Consequently, a particular accommodated state may besaid to be associated with a particular one of rendering planes 306,with has an associated focal distance, such that objects or parts ofobjects in a particular rendering plane are in focus when the eye is inthe accommodated state for that rendering plane. In some embodiments,three-dimensional imagery may be simulated by providing differentpresentations of an image for each of the eyes 302 and 304, and also byproviding different presentations of the image corresponding to each ofthe rendering planes. While shown as being separate for clarity ofillustration, it will be appreciated that the fields of view of the eyes302 and 304 may overlap, for example, as distance along the z-axisincreases. In addition, while shown as flat for the ease ofillustration, it will be appreciated that the contours of a renderingplane may be curved in physical space, such that all features in arendering plane are in focus with the eye in a particular accommodatedstate. Without being limited by theory, it is believed that the humaneye typically can interpret a finite number of rendering planes toprovide depth perception. Consequently, a highly believable simulationof perceived depth may be achieved by providing, to the eye, differentpresentations of an image corresponding to each of these limited numberof rendering planes.

Waveguide Stack Assembly

FIG. 4 illustrates an example of a waveguide stack for outputting imageinformation to a user. A wearable system 400 includes a stack ofwaveguides, or stacked waveguide assembly 480 that may be utilized toprovide three-dimensional perception to the eye/brain using a pluralityof waveguides 432 b, 434 b, 436 b, 438 b, 4400 b. In some embodiments,the wearable system 400 may correspond to wearable system 200 of FIG. 2,with FIG. 4 schematically showing some parts of that wearable system 200in greater detail. For example, in some embodiments, the waveguideassembly 480 may be integrated into the display 220 of FIG. 2.

With continued reference to FIG. 4, the waveguide assembly 480 may alsoinclude a plurality of features 458, 456, 454, 452 between thewaveguides. In some embodiments, the features 458, 456, 454, 452 may belenses. In other embodiments, the features 458, 456, 454, 452 may not belenses. Rather, they may simply be spacers (e.g., cladding layers orstructures for forming air gaps).

The waveguides 432 b, 434 b, 436 b, 438 b, 440 b or the plurality oflenses 458, 456, 454, 452 may be configured to send image information tothe eye with various levels of wavefront curvature or light raydivergence. Each waveguide level may be associated with a particularrendering plane and may be configured to output image informationcorresponding to that rendering plane. Image injection devices 420, 422,424, 426, 428 may be utilized to inject image information into thewaveguides 440 b, 438 b, 436 b, 434 b, 432 b, each of which may beconfigured to distribute incoming light across each respectivewaveguide, for output toward the eye 410. Light exits an output surfaceof the image injection devices 420, 422, 424, 426, 428 and is injectedinto a corresponding input edge of the waveguides 440 b, 438 b, 436 b,434 b, 432 b. In some embodiments, a single beam of light (e.g., acollimated beam) may be injected into each waveguide to output an entirefield of cloned collimated beams that are directed toward the eye 410 atparticular angles (and amounts of divergence) corresponding to therendering plane associated with a particular waveguide.

In some embodiments, the image injection devices 420, 422, 424, 426, 428are discrete displays that each produce image information for injectioninto a corresponding waveguide 440 b, 438 b, 436 b, 434 b, 432 b,respectively. In some other embodiments, the image injection devices420, 422, 424, 426, 428 are the output ends of a single multiplexeddisplay which may, e.g., pipe image information via one or more opticalconduits (such as fiber optic cables) to each of the image injectiondevices 420, 422, 424, 426, 428.

A controller 460 controls the operation of the stacked waveguideassembly 480 and the image injection devices 420, 422, 424, 426, 428.The controller 460 includes programming (e.g., instructions in anon-transitory computer-readable medium) that regulates the timing andprovision of image information to the waveguides 440 b, 438 b, 436 b,434 b, 432 b. In some embodiments, the controller 460 may be a singleintegral device, or a distributed system connected by wired or wirelesscommunication channels. The controller 460 may be part of the processingmodules 260 or 270 (illustrated in FIG. 2) in some embodiments.

The waveguides 440 b, 438 b, 436 b, 434 b, 432 b may be configured topropagate light within each respective waveguide by total internalreflection (TIR). The waveguides 440 b, 438 b, 436 b, 434 b, 432 b mayeach be planar or have another shape (e.g., curved), with major top andbottom surfaces and edges extending between those major top and bottomsurfaces. In the illustrated configuration, the waveguides 440 b, 438 b,436 b, 434 b, 432 b may each include light extracting optical elements440 a, 438 a, 436 a, 434 a, 432 a that are configured to extract lightout of a waveguide by redirecting the light, propagating within eachrespective waveguide, out of the waveguide to output image informationto the eye 410. Extracted light may also be referred to as outcoupledlight, and light extracting optical elements may also be referred to asoutcoupling optical elements. An extracted beam of light is outputted bythe waveguide at locations at which the light propagating in thewaveguide strikes a light redirecting element. The light extractingoptical elements (440 a, 438 a, 436 a, 434 a, 432 a) may, for example,be reflective or diffractive optical features. While illustrateddisposed at the bottom major surfaces of the waveguides 440 b, 438 b,436 b, 434 b, 432 b for ease of description and drawing clarity, in someembodiments, the light extracting optical elements 440 a, 438 a, 436 a,434 a, 432 a may be disposed at the top or bottom major surfaces, or maybe disposed directly in the volume of the waveguides 440 b, 438 b, 436b, 434 b, 432 b. In some embodiments, the light extracting opticalelements 440 a, 438 a, 436 a, 434 a, 432 a may be formed in a layer ofmaterial that is attached to a transparent substrate to form thewaveguides 440 b, 438 b, 436 b, 434 b, 432 b. In some other embodiments,the waveguides 440 b, 438 b, 436 b, 434 b, 432 b may be a monolithicpiece of material and the light extracting optical elements 440 a, 438a, 436 a, 434 a, 432 a may be formed on a surface or in the interior ofthat piece of material.

With continued reference to FIG. 4, as discussed herein, each waveguide440 b, 438 b, 436 b, 434 b, 432 b is configured to output light to forman image corresponding to a particular rendering plane. For example, thewaveguide 432 b nearest the eye may be configured to deliver collimatedlight, as injected into such waveguide 432 b, to the eye 410. Thecollimated light may be representative of the optical infinity focalplane. The next waveguide up 434 b may be configured to send outcollimated light which passes through the first lens 452 (e.g., anegative lens) before it can reach the eye 410. First lens 452 may beconfigured to create a slight convex wavefront curvature so that theeye/brain interprets light coming from that next waveguide up 434 b ascoming from a first focal plane closer inward toward the eye 410 fromoptical infinity. Similarly, the third up waveguide 436 b passes itsoutput light through both the first lens 452 and second lens 454 beforereaching the eye 410. The combined optical power of the first and secondlenses 452 and 454 may be configured to create another incrementalamount of wavefront curvature so that the eye/brain interprets lightcoming from the third waveguide 436 b as coming from a second focalplane that is even closer inward toward the person from optical infinitythan was light from the next waveguide up 434 b.

The other waveguide layers (e.g., waveguides 438 b, 440 b) and lenses(e.g., lenses 456, 458) are similarly configured, with the highestwaveguide 440 b in the stack sending its output through all of thelenses between it and the eye for an aggregate focal powerrepresentative of the closest focal plane to the person. To compensatefor the stack of lenses 458, 456, 454, 452 when viewing/interpretinglight coming from the world 470 on the other side of the stackedwaveguide assembly 480, a compensating lens layer 430 may be disposed atthe top of the stack to compensate for the aggregate power of the lensstack 458, 456, 454, 452 below. Such a configuration provides as manyperceived focal planes as there are available waveguide/lens pairings.Both the light extracting optical elements of the waveguides and thefocusing aspects of the lenses may be static (e.g., not dynamic orelectro-active). In some alternative embodiments, either or both may bedynamic using electro-active features.

With continued reference to FIG. 4, the light extracting opticalelements 440 a, 438 a, 436 a, 434 a, 432 a may be configured to bothredirect light out of their respective waveguides and to output thislight with the appropriate amount of divergence or collimation for aparticular rendering plane associated with the waveguide. As a result,waveguides having different associated rendering planes may havedifferent configurations of light extracting optical elements, whichoutput light with a different amount of divergence depending on theassociated rendering plane. In some embodiments, as discussed herein,the light extracting optical elements 440 a, 438 a, 436 a, 434 a, 432 amay be volumetric or surface features, which may be configured to outputlight at specific angles. For example, the light extracting opticalelements 440 a, 438 a, 436 a, 434 a, 432 a may be volume holograms,surface holograms, and/or diffraction gratings. Light extracting opticalelements, such as diffraction gratings, are described in U.S. PatentPublication No. 2015/0178939, published Jun. 25, 2015, which isincorporated by reference herein in its entirety.

In some embodiments, the light extracting optical elements 440 a, 438 a,436 a, 434 a, 432 a are diffractive features that form a diffractionpattern, or “diffractive optical element” (also referred to herein as a“DOE”). Preferably, the DOE has a relatively low diffraction efficiencyso that only a portion of the light of the beam is deflected away towardthe eye 410 with each intersection of the DOE, while the rest continuesto move through a waveguide via total internal reflection. The lightcarrying the image information can thus be divided into a number ofrelated exit beams that exit the waveguide at a multiplicity oflocations and the result is a fairly uniform pattern of exit emissiontoward the eye 304 for this particular collimated beam bouncing aroundwithin a waveguide.

In some embodiments, one or more DOEs may be switchable between “on”state in which they actively diffract, and “off” state in which they donot significantly diffract. For instance, a switchable DOE may comprisea layer of polymer dispersed liquid crystal, in which microdropletscomprise a diffraction pattern in a host medium, and the refractiveindex of the microdroplets can be switched to substantially match therefractive index of the host material (in which case the pattern doesnot appreciably diffract incident light) or the microdroplet can beswitched to an index that does not match that of the host medium (inwhich case the pattern actively diffracts incident light).

In some embodiments, the number and distribution of rendering planes ordepth of field may be varied dynamically based on the pupil sizes ororientations of the eyes of the viewer. Depth of field may changeinversely with a viewer's pupil size. As a result, as the sizes of thepupils of the viewer's eyes decrease, the depth of field increases suchthat one plane that is not discernible because the location of thatplane is beyond the depth of focus of the eye may become discernible andappear more in focus with reduction of pupil size and commensurate withthe increase in depth of field. Likewise, the number of spaced apartrendering planes used to present different images to the viewer may bedecreased with the decreased pupil size. For example, a viewer may notbe able to clearly perceive the details of both a first rendering planeand a second rendering plane at one pupil size without adjusting theaccommodation of the eye away from one rendering plane and to the otherrendering plane. These two rendering planes may, however, besufficiently in focus at the same time to the user at another pupil sizewithout changing accommodation.

In some embodiments, the display system may vary the number ofwaveguides receiving image information based upon determinations ofpupil size or orientation, or upon receiving electrical signalsindicative of particular pupil size or orientation. For example, if theuser's eyes are unable to distinguish between two rendering planesassociated with two waveguides, then the controller 460 may beconfigured or programmed to cease providing image information to one ofthese waveguides. Advantageously, this may reduce the processing burdenon the system, thereby increasing the responsiveness of the system. Inembodiments in which the DOEs for a waveguide are switchable between theon and off states, the DOEs may be switched to the off state when thewaveguide does receive image information.

In some embodiments, it may be desirable to have an exit beam meet thecondition of having a diameter that is less than the diameter of the eyeof a viewer. However, meeting this condition may be challenging in viewof the variability in size of the viewer's pupils. In some embodiments,this condition is met over a wide range of pupil sizes by varying thesize of the exit beam in response to determinations of the size of theviewer's pupil. For example, as the pupil size decreases, the size ofthe exit beam may also decrease. In some embodiments, the exit beam sizemay be varied using a variable aperture.

The wearable system 400 can include an outward-facing imaging system 464(e.g., a digital camera) that images a portion of the world 470. Thisportion of the world 470 may be referred to as the field of view (FOV)of a world camera and the imaging system 464 is sometimes referred to asan FOV camera. The entire region available for viewing or imaging by aviewer may be referred to as the field of regard (FOR). The FOR mayinclude 4π steradians of solid angle surrounding the wearable system 400because the wearer can move his body, head, or eyes to perceivesubstantially any direction in space. In other contexts, the wearer'smovements may be more constricted, and accordingly the wearer's FOR maysubtend a smaller solid angle. Images obtained from the outward-facingimaging system 464 can be used to track gestures made by the user (e.g.,hand or finger gestures), detect objects in the world 470 in front ofthe user, and so forth.

The wearable system 400 can also include an inward-facing imaging system462 (e.g., a digital camera), which observes the movements of the user,such as the eye movements and the facial movements. The inward-facingimaging system 462 may be used to capture images of the eye 410 todetermine the size and/or orientation of the pupil of the eye 304. Theinward-facing imaging system 462 can be used to obtain images for use indetermining the direction the user is looking (e.g., eye pose) or forbiometric identification of the user (e.g., via iris identification). Insome embodiments, at least one camera may be utilized for each eye, toseparately determine the pupil size or eye pose of each eyeindependently, thereby allowing the presentation of image information toeach eye to be dynamically tailored to that eye. In some otherembodiments, the pupil diameter or orientation of only a single eye 410(e.g., using only a single camera per pair of eyes) is determined andassumed to be similar for both eyes of the user. The images obtained bythe inward-facing imaging system 462 may be analyzed to determine theuser's eye pose or mood, which can be used by the wearable system 400 todecide which audio or visual content should be presented to the user.The wearable system 400 may also determine head pose (e.g., headposition or head orientation) using sensors such as IMUs,accelerometers, gyroscopes, etc.

The wearable system 400 can include a user input device 466 by which theuser can input commands to the controller 460 to interact with thewearable system 400. For example, the user input device 466 can includea trackpad, a touchscreen, a joystick, a multiple degree-of-freedom(DOF) controller, a capacitive sensing device, a game controller, akeyboard, a mouse, a directional pad (D-pad), a wand, a haptic device, atotem (e.g., functioning as a virtual user input device), and so forth.A multi-DOF controller can sense user input in some or all possibletranslations (e.g., left/right, forward/backward, or up/down) orrotations (e.g., yaw, pitch, or roll) of the controller. A multi-DOFcontroller which supports the translation movements may be referred toas a 3DOF while a multi-DOF controller which supports the translationsand rotations may be referred to as 6DOF. In some cases, the user mayuse a finger (e.g., a thumb) to press or swipe on a touch-sensitiveinput device to provide input to the wearable system 400 (e.g., toprovide user input to a user interface provided by the wearable system400). The user input device 466 may be held by the user's hand duringthe use of the wearable system 400. The user input device 466 can be inwired or wireless communication with the wearable system 400.

FIG. 5 shows an example of exit beams outputted by a waveguide. Onewaveguide is illustrated, but it will be appreciated that otherwaveguides in the waveguide assembly 480 may function similarly, wherethe waveguide assembly 480 includes multiple waveguides. Light 520 isinjected into the waveguide 432 b at the input edge 432 c of thewaveguide 432 b and propagates within the waveguide 432 b by TIR. Atpoints where the light 520 impinges on the DOE 432 a, a portion of thelight exits the waveguide as exit beams 510. The exit beams 510 areillustrated as substantially parallel but they may also be redirected topropagate to the eye 410 at an angle (e.g., forming divergent exitbeams), depending on the rendering plane associated with the waveguide432 b. It will be appreciated that substantially parallel exit beams maybe indicative of a waveguide with light extracting optical elements thatoutcouple light to form images that appear to be set on a renderingplane at a large distance (e.g., optical infinity) from the eye 410.Other waveguides or other sets of light extracting optical elements mayoutput an exit beam pattern that is more divergent, which would requirethe eye 410 to accommodate to a closer distance to bring it into focuson the retina and would be interpreted by the brain as light from adistance closer to the eye 410 than optical infinity.

FIG. 6 is a schematic diagram showing an optical system including awaveguide apparatus, an optical coupler subsystem to optically couplelight to or from the waveguide apparatus, and a control subsystem, usedin the generation of a multi-focal volumetric display, image, or lightfield. The optical system can include a waveguide apparatus, an opticalcoupler subsystem to optically couple light to or from the waveguideapparatus, and a control subsystem. The optical system can be used togenerate a multi-focal volumetric, image, or light field. The opticalsystem can include one or more primary planar waveguides 632 a (only oneis shown in FIG. 6) and one or more DOEs 632 b associated with each ofat least some of the primary waveguides 632 a. The planar waveguides 632b can be similar to the waveguides 432 b, 434 b, 436 b, 438 b, 440 bdiscussed with reference to FIG. 4. The optical system may employ adistribution waveguide apparatus to relay light along a first axis(vertical or Y-axis in view of FIG. 6), and expand the light's effectiveexit pupil along the first axis (e.g., Y-axis). The distributionwaveguide apparatus may, for example, include a distribution planarwaveguide 622 b and at least one DOE 622 a (illustrated by doubledash-dot line) associated with the distribution planar waveguide 622 b.The distribution planar waveguide 622 b may be similar or identical inat least some respects to the primary planar waveguide 632 b, having adifferent orientation therefrom. Likewise, at least one DOE 622 a may besimilar or identical in at least some respects to the DOE 632 a. Forexample, the distribution planar waveguide 622 b or DOE 622 a may becomprised of the same materials as the primary planar waveguide 632 b orDOE 632 a, respectively. Embodiments of the optical display system 600shown in FIG. 6 can be integrated into the wearable system 200 shown inFIG. 2.

The relayed and exit-pupil expanded light may be optically coupled fromthe distribution waveguide apparatus into the one or more primary planarwaveguides 632 b. The primary planar waveguide 632 b can relay lightalong a second axis, preferably orthogonal to first axis (e.g.,horizontal or X-axis in view of FIG. 6). Notably, the second axis can bea non-orthogonal axis to the first axis. The primary planar waveguide632 b expands the light's effective exit pupil along that second axis(e.g., X-axis). For example, the distribution planar waveguide 622 b canrelay and expand light along the vertical or Y-axis, and pass that lightto the primary planar waveguide 632 b which can relay and expand lightalong the horizontal or X-axis.

The optical system may include one or more sources of colored light(e.g., red, green, and blue laser light) 610 which may be opticallycoupled into a proximal end of a single mode optical fiber 640. A distalend of the optical fiber 640 may be threaded or received through ahollow tube 642 of piezoelectric material. The distal end protrudes fromthe tube 642 as fixed-free flexible cantilever 644. The piezoelectrictube 642 can be associated with four quadrant electrodes (notillustrated). The electrodes may, for example, be plated on the outside,outer surface or outer periphery or diameter of the tube 642. A coreelectrode (not illustrated) may also be located in a core, center, innerperiphery or inner diameter of the tube 642.

Drive electronics 650, for example electrically coupled via wires 660,drive opposing pairs of electrodes to bend the piezoelectric tube 642 intwo axes independently. The protruding distal tip of the optical fiber644 has mechanical modes of resonance. The frequencies of resonance candepend upon a diameter, length, and material properties of the opticalfiber 644. By vibrating the piezoelectric tube 642 near a first mode ofmechanical resonance of the fiber cantilever 644, the fiber cantilever644 can be caused to vibrate, and can sweep through large deflections.

By stimulating resonant vibration in two axes, the tip of the fibercantilever 644 is scanned biaxially in an area filling two-dimensional(2D) scan. By modulating an intensity of light source(s) 610 insynchrony with the scan of the fiber cantilever 644, light emerging fromthe fiber cantilever 644 can form an image. Descriptions of such a setup are provided in U.S. Patent Publication No. 2014/0003762, which isincorporated by reference herein in its entirety.

A component of an optical coupler subsystem can collimate the lightemerging from the scanning fiber cantilever 644. The collimated lightcan be reflected by mirrored surface 648 into the narrow distributionplanar waveguide 622 b which contains the at least one diffractiveoptical element (DOE) 622 a. The collimated light can propagatevertically (relative to the view of FIG. 6) along the distributionplanar waveguide 622 b by TIR, and in doing so repeatedly intersectswith the DOE 622 a. The DOE 622 a preferably has a low diffractionefficiency. This can cause a fraction (e.g., 10%) of the light to bediffracted toward an edge of the larger primary planar waveguide 632 bat each point of intersection with the DOE 622 a, and a fraction of thelight to continue on its original trajectory down the length of thedistribution planar waveguide 622 b via TIR.

At each point of intersection with the DOE 622 a, additional light canbe diffracted toward the entrance of the primary waveguide 632 b. Bydividing the incoming light into multiple outcoupled sets, the exitpupil of the light can be expanded vertically by the DOE 4 in thedistribution planar waveguide 622 b. This vertically expanded lightcoupled out of distribution planar waveguide 622 b can enter the edge ofthe primary planar waveguide 632 b.

Light entering primary waveguide 632 b can propagate horizontally(relative to the view of FIG. 6) along the primary waveguide 632 b viaTIR. As the light intersects with DOE 632 a at multiple points as itpropagates horizontally along at least a portion of the length of theprimary waveguide 632 b via TIR. The DOE 632 a may advantageously bedesigned or configured to have a phase profile that is a summation of alinear diffraction pattern and a radially symmetric diffractive pattern,to produce both deflection and focusing of the light. The DOE 632 a mayadvantageously have a low diffraction efficiency (e.g., 10%), so thatonly a portion of the light of the beam is deflected toward the eye ofthe view with each intersection of the DOE 632 a while the rest of thelight continues to propagate through the primary waveguide 632 b viaTIR.

At each point of intersection between the propagating light and the DOE632 a, a fraction of the light is diffracted toward the adjacent face ofthe primary waveguide 632 b allowing the light to escape the TIR, andemerge from the face of the primary waveguide 632 b. In someembodiments, the radially symmetric diffraction pattern of the DOE 632 aadditionally imparts a focus level to the diffracted light, both shapingthe light wavefront (e.g., imparting a curvature) of the individual beamas well as steering the beam at an angle that matches the designed focuslevel.

Accordingly, these different pathways can cause the light to be coupledout of the primary planar waveguide 632 b by a multiplicity of DOEs 632a at different angles, focus levels, and/or yielding different fillpatterns at the exit pupil. Different fill patterns at the exit pupilcan be beneficially used to create a light field display with multiplerendering planes. Each layer in the waveguide assembly or a set oflayers (e.g., 3 layers) in the stack may be employed to generate arespective color (e.g., red, blue, green). Thus, for example, a firstset of three adjacent layers may be employed to respectively producered, blue and green light at a first focal depth. A second set of threeadjacent layers may be employed to respectively produce red, blue andgreen light at a second focal depth. Multiple sets may be employed togenerate a full 3D or 4D color image light field with various focaldepths.

Other Components of the Wearable System

In many implementations, the wearable system may include othercomponents in addition or in alternative to the components of thewearable system described above. The wearable system may, for example,include one or more haptic devices or components. The haptic devices orcomponents may be operable to provide a tactile sensation to a user. Forexample, the haptic devices or components may provide a tactilesensation of pressure or texture when touching virtual content (e.g.,virtual objects, virtual tools, other virtual constructs). The tactilesensation may replicate a feel of a physical object which a virtualobject represents, or may replicate a feel of an imagined object orcharacter (e.g., a dragon) which the virtual content represents. In someimplementations, haptic devices or components may be worn by the user(e.g., a user wearable glove). In some implementations, haptic devicesor components may be held by the user.

The wearable system may, for example, include one or more physicalobjects which are manipulable by the user to allow input or interactionwith the wearable system. These physical objects may be referred toherein as totems. Some totems may take the form of inanimate objects,such as for example, a piece of metal or plastic, a wall, a surface oftable. In certain implementations, the totems may not actually have anyphysical input structures (e.g., keys, triggers, joystick, trackball,rocker switch). Instead, the totem may simply provide a physicalsurface, and the wearable system may render a user interface so as toappear to a user to be on one or more surfaces of the totem. Forexample, the wearable system may render an image of a computer keyboardand trackpad to appear to reside on one or more surfaces of a totem. Forexample, the wearable system may render a virtual computer keyboard andvirtual trackpad to appear on a surface of a thin rectangular plate ofaluminum which serves as a totem. The rectangular plate does not itselfhave any physical keys or trackpad or sensors. However, the wearablesystem may detect user manipulation or interaction or touches with therectangular plate as selections or inputs made via the virtual keyboardor virtual trackpad. The user input device 466 (shown in FIG. 4) may bean embodiment of a totem, which may include a trackpad, a touchpad, atrigger, a joystick, a trackball, a rocker or virtual switch, a mouse, akeyboard, a multi-degree-of-freedom controller, or another physicalinput device. A user may use the totem, alone or in combination withposes, to interact with the wearable system or other users.

Examples of haptic devices and totems usable with the wearable devices,HMD, and display systems of the present disclosure are described in U.S.Patent Publication No. 2015/0016777, which is incorporated by referenceherein in its entirety.

Example Wearable Systems, Environments, and Interfaces

A wearable system may employ various mapping related techniques in orderto achieve high depth of field in the rendered light fields. In mappingout the virtual world, it is advantageous to know all the features andpoints in the real world to accurately portray virtual objects inrelation to the real world. To this end, FOV images captured from usersof the wearable system can be added to a world model by including newpictures that convey information about various points and features ofthe real world. For example, the wearable system can collect a set ofmap points (such as 2D points or 3D points) and find new map points torender a more accurate version of the world model. The world model of afirst user can be communicated (e.g., over a network such as a cloudnetwork) to a second user so that the second user can experience theworld surrounding the first user.

FIG. 7 is a block diagram of an example of an MR environment 700. The MRenvironment 700 may be configured to receive input (e.g., visual input702 from the user's wearable system, stationary input 704 such as roomcameras, sensory input 706 from various sensors, gestures, totems, eyetracking, user input from the user input device 466 etc.) from one ormore user wearable systems (e.g., wearable system 200 or display system220) or stationary room systems (e.g., room cameras, etc.). The wearablesystems can use various sensors (e.g., accelerometers, gyroscopes,temperature sensors, movement sensors, depth sensors, GPS sensors,inward-facing imaging system, outward-facing imaging system, etc.) todetermine the location and various other attributes of the environmentof the user. This information may further be supplemented withinformation from stationary cameras in the room that may provide imagesor various cues from a different point of view. The image data acquiredby the cameras (such as the room cameras and/or the cameras of theoutward-facing imaging system) may be reduced to a set of mappingpoints.

One or more object recognizers 708 can crawl through the received data(e.g., the collection of points) and recognize or map points, tagimages, attach semantic information to objects with the help of a mapdatabase 710. The map database 710 may comprise various points collectedover time and their corresponding objects. The various devices and themap database can be connected to each other through a network (e.g.,LAN, WAN, etc.) to access the cloud.

Based on this information and collection of points in the map database,the object recognizers 708 a to 708 n may recognize objects in anenvironment. For example, the object recognizers can recognize faces,persons, windows, walls, user input devices, televisions, other objectsin the user's environment, etc. One or more object recognizers may bespecialized for object with certain characteristics. For example, theobject recognizer 708 a may be used to recognize faces, while anotherobject recognizer may be used recognize totems.

The object recognitions may be performed using a variety of computervision techniques. For example, the wearable system can analyze theimages acquired by the outward-facing imaging system 464 (shown in FIG.4) to perform scene reconstruction, event detection, video tracking,object recognition, object pose estimation, learning, indexing, motionestimation, or image restoration, etc. One or more computer visionalgorithms may be used to perform these tasks. Non-limiting examples ofcomputer vision algorithms include: Scale-invariant feature transform(SIFT), speeded up robust features (SURF), oriented FAST and rotatedBRIEF (ORB), binary robust invariant scalable keypoints (BRISK), fastretina keypoint (FREAK), Viola-Jones algorithm, Eigenfaces approach,Lucas-Kanade algorithm, Horn-Schunk algorithm, Mean-shift algorithm,visual simultaneous location and mapping (vSLAM) techniques, asequential Bayesian estimator (e.g., Kalman filter, extended Kalmanfilter, etc.), bundle adjustment, Adaptive thresholding (and otherthresholding techniques), Iterative Closest Point (ICP), Semi GlobalMatching (SGM), Semi Global Block Matching (SGBM), Feature PointHistograms, various machine learning algorithms (such as e.g., supportvector machine, k-nearest neighbors algorithm, Naive Bayes, neuralnetwork (including convolutional or deep neural networks), or othersupervised/unsupervised models, etc.), and so forth.

The object recognitions can additionally or alternatively be performedby a variety of machine learning algorithms. Once trained, the machinelearning algorithm can be stored by the HMD. Some examples of machinelearning algorithms can include supervised or non-supervised machinelearning algorithms, including regression algorithms (such as, forexample, Ordinary Least Squares Regression), instance-based algorithms(such as, for example, Learning Vector Quantization), decision treealgorithms (such as, for example, classification and regression trees),Bayesian algorithms (such as, for example, Naive Bayes), clusteringalgorithms (such as, for example, k-means clustering), association rulelearning algorithms (such as, for example, a-priori algorithms),artificial neural network algorithms (such as, for example, Perceptron),deep learning algorithms (such as, for example, Deep Boltzmann Machine,or deep neural network), dimensionality reduction algorithms (such as,for example, Principal Component Analysis), ensemble algorithms (suchas, for example, Stacked Generalization), and/or other machine learningalgorithms. In some embodiments, individual models can be customized forindividual data sets. For example, the wearable device can generate orstore a base model. The base model may be used as a starting point togenerate additional models specific to a data type (e.g., a particularuser in the telepresence session), a data set (e.g., a set of additionalimages obtained of the user in the telepresence session), conditionalsituations, or other variations. In some embodiments, the wearable HMDcan be configured to utilize a plurality of techniques to generatemodels for analysis of the aggregated data. Other techniques may includeusing pre-defined thresholds or data values.

Based on this information and collection of points in the map database,the object recognizers 708 a to 708 n may recognize objects andsupplement objects with semantic information to give life to theobjects. For example, if the object recognizer recognizes a set ofpoints to be a door, the system may attach some semantic information(e.g., the door has a hinge and has a 90 degree movement about thehinge). If the object recognizer recognizes a set of points to be amirror, the system may attach semantic information that the mirror has areflective surface that can reflect images of objects in the room. Overtime the map database grows as the system (which may reside locally ormay be accessible through a wireless network) accumulates more data fromthe world. Once the objects are recognized, the information may betransmitted to one or more wearable systems. For example, the MRenvironment 700 may include information about a scene happening inCalifornia. The environment 700 may be transmitted to one or more usersin New York. Based on data received from an FOV camera and other inputs,the object recognizers and other software components can map the pointscollected from the various images, recognize objects etc., such that thescene may be accurately “passed over” to a second user, who may be in adifferent part of the world. The environment 700 may also use atopological map for localization purposes.

FIG. 8 is a process flow diagram of an example of a method 800 ofrendering virtual content in relation to recognized objects. The method800 describes how a virtual scene may be represented to a user of thewearable system. The user may be geographically remote from the scene.For example, the user may be New York, but may want to view a scene thatis presently going on in California, or may want to go on a walk with afriend who resides in California.

At block 810, the wearable system may receive input from the user andother users regarding the environment of the user. This may be achievedthrough various input devices, and knowledge already possessed in themap database. The user's FOV camera, sensors, GPS, eye tracking, etc.,convey information to the system at block 810. The system may determinesparse points based on this information at block 820. The sparse pointsmay be used in determining pose data (e.g., head pose, eye pose, bodypose, or hand gestures) that can be used in displaying and understandingthe orientation and position of various objects in the user'ssurroundings. The object recognizers 708 a-708 n may crawl through thesecollected points and recognize one or more objects using a map databaseat block 830. This information may then be conveyed to the user'sindividual wearable system at block 840, and the desired virtual scenemay be accordingly displayed to the user at block 850. For example, thedesired virtual scene (e.g., user in CA) may be displayed at theappropriate orientation, position, etc., in relation to the variousobjects and other surroundings of the user in New York.

FIG. 9 is a block diagram of another example of a wearable system. Inthis example, the wearable system 900 comprises a map, which may includemap data for the world. The map may partly reside locally on thewearable system, and may partly reside at networked storage locationsaccessible by wired or wireless network (e.g., in a cloud system). Apose process 910 (e.g., head or eye pose) may be executed on thewearable computing architecture (e.g., processing module 260 orcontroller 460) and utilize data from the map to determine position andorientation of the wearable computing hardware or user. Pose data may becomputed from data collected on the fly as the user is experiencing thesystem and operating in the world. The data may comprise images, datafrom sensors (such as inertial measurement units, which generallycomprise accelerometer and gyroscope components) and surface informationpertinent to objects in the real or virtual environment.

A sparse point representation may be the output of a simultaneouslocalization and mapping (SLAM or V-SLAM, referring to a configurationwherein the input is images/visual only) process. The system can beconfigured to not only find out where in the world the variouscomponents are, but what the world is made of. Pose may be a buildingblock that achieves many goals, including populating the map and usingthe data from the map.

In one embodiment, a sparse point position may not be completelyadequate on its own, and further information may be needed to produce amultifocal AR, VR, or MR experience. Dense representations, generallyreferring to depth map information, may be utilized to fill this gap atleast in part. Such information may be computed from a process referredto as Stereo 940, wherein depth information is determined using atechnique such as triangulation or time-of-flight sensing. Imageinformation and active patterns (such as infrared patterns created usingactive projectors) may serve as input to the Stereo process 940. Asignificant amount of depth map information may be fused together, andsome of this may be summarized with a surface representation. Forexample, mathematically definable surfaces may be efficient (e.g.,relative to a large point cloud) and digestible inputs to otherprocessing devices like game engines. Thus, the output of the stereoprocess (e.g., a depth map) 940 may be combined in the fusion process930. Pose may be an input to this fusion process 930 as well, and theoutput of fusion 930 becomes an input to populating the map process 920.Sub-surfaces may connect with each other, such as in topographicalmapping, to form larger surfaces, and the map becomes a large hybrid ofpoints and surfaces.

To resolve various aspects in a mixed reality process 960, variousinputs may be utilized. For example, in the embodiment depicted in FIG.9, Game parameters may be inputs to determine that the user of thesystem is playing a monster battling game with one or more monsters atvarious locations, monsters dying or running away under variousconditions (such as if the user shoots the monster), walls or otherobjects at various locations, and the like. The world map may includeinformation regarding where such objects are relative to each other, tobe another valuable input to mixed reality. Pose relative to the worldbecomes an input as well and plays a key role to almost any interactivesystem.

Controls or inputs from the user are another input to the wearablesystem 900. As described herein, user inputs can include visual input,gestures, totems, audio input, sensory input, etc. In order to movearound or play a game, for example, the user may need to instruct thewearable system 900 regarding what he or she wants to do. Beyond justmoving oneself in space, there are various forms of user controls thatmay be utilized. In one embodiment, a totem (e.g. a user input device),or an object such as a toy gun may be held by the user and tracked bythe system. The system preferably will be configured to know that theuser is holding the item and understand what kind of interaction theuser is having with the item (e.g., if the totem or object is a gun, thesystem may be configured to understand location and orientation, as wellas whether the user is clicking a trigger or other sensed button orelement which may be equipped with a sensor, such as an IMU, which mayassist in determining what is going on, even when such activity is notwithin the field of view of any of the cameras.)

Hand gesture tracking or recognition may also provide input information.The wearable system 900 may be configured to track and interpret handgestures for button presses, for gesturing left or right, stop, grab,hold, etc. For example, in one configuration, the user may want to flipthrough emails or a calendar in a non-gaming environment, or do a “fistbump” with another person or player. The wearable system 900 may beconfigured to leverage a minimum amount of hand gesture, which may ormay not be dynamic. For example, the gestures may be simple staticgestures like open hand for stop, thumbs up for ok, thumbs down for notok; or a hand flip right, or left, or up/down for directional commands.

Eye tracking is another input (e.g., tracking where the user is lookingto control the display technology to render at a specific depth orrange). In one embodiment, vergence of the eyes may be determined usingtriangulation, and then using a vergence/accommodation model developedfor that particular person, accommodation may be determined.

Voice recognition is another input, which can be used alone or incombination with other inputs (e.g., totem tracking, eye tracking,gesture tracking, etc.). The system 900 can include an audio sensor 232(e.g., a microphone) that receives an audio stream from the environment.The received audio stream can be processed (e.g., by processing modules260, 270 or central server 1650) to recognize a user's voice (from othervoices or background audio), to extract commands, subjects, parameters,etc. from the audio stream. For example, the system 900 may identifyfrom an audio stream that the phrase “move that there” was said,identify that this phrase was said by the wearer of the system 900(rather than another person in the user's environment), and extract fromthe phrase that there is an executable command (“move”) and an object tobe moved (“that”) to a location (“there”). The object to be operatedupon by the command may be referred to as the subject of the command,and other information provided as a parameter to the command. In thisexample, the location of where the object is to be moved is a parameterfor the move command. Parameters can include, for example, a location, atime, other objects to be interacted with (e.g., “move that next to thered chair” or “give the magic wand to Linda”), how the command is to beexecuted (e.g., “play my music using the upstairs speakers”), and soforth.

As another example, the system 900 can process an audio stream withspeech recognition techniques to input a string of text or to modifycontent of a text. The system 900 can incorporate speaker recognitiontechnology to determine who is speaking as well as speech recognitiontechnology to determine what is being said. Voice recognition techniquescan include hidden Markov models, Gaussian mixture models, patternmatching algorithms, neural networks, matrix representation, VectorQuantization, speaker diarisation, decision trees, and dynamic timewarping (DTW) techniques, alone or in combination. Voice recognitiontechniques can also include anti-speaker techniques, such as cohortmodels, and world models. Spectral features may be used in representingspeaker characteristics.

With regard to the camera systems, the example wearable system 900 shownin FIG. 9 can include three pairs of cameras: a relative wide FOV orpassive SLAM pair of cameras arranged to the sides of the user's face, adifferent pair of cameras oriented in front of the user to handle thestereo imaging process 940 and also to capture hand gestures andtotem/object tracking in front of the user's face. The FOV cameras andthe pair of cameras for the stereo process 940 may be a part of theoutward-facing imaging system 464 (shown in FIG. 4). The wearable system900 can include eye tracking cameras (which may be a part of aninward-facing imaging system 462 shown in FIG. 4) oriented toward theeyes of the user in order to triangulate eye vectors and otherinformation. The wearable system 900 may also comprise one or moretextured light projectors (such as infrared (IR) projectors) to injecttexture into a scene.

FIG. 10 is a process flow diagram of an example of a method 1000 fordetermining user input to a wearable system. In this example, the usermay interact with a totem. The user may have multiple totems. Forexample, the user may have designated one totem for a social mediaapplication, another totem for playing games, etc. At block 1010, thewearable system may detect a motion of a totem. The movement of thetotem may be recognized through the outward facing system or may bedetected through sensors (e.g., haptic glove, image sensors, handtracking devices, eye-tracking cameras, head pose sensors, etc.).

Based at least partly on the detected gesture, eye pose, head pose, orinput through the totem, the wearable system detects a position,orientation, and/or movement of the totem (or the user's eyes or head orgestures) with respect to a reference frame, at block 1020. Thereference frame may be a set of map points based on which the wearablesystem translates the movement of the totem (or the user) to an actionor command. At block 1030, the user's interaction with the totem ismapped. Based on the mapping of the user interaction with respect to thereference frame 1020, the system determines the user input at block1040.

For example, the user may move a totem or physical object back and forthto signify turning a virtual page and moving on to a next page or movingfrom one user interface (UI) display screen to another UI screen. Asanother example, the user may move their head or eyes to look atdifferent real or virtual objects in the user's FOR. If the user's gazeat a particular real or virtual object is longer than a threshold time,the real or virtual object may be selected as the user input. In someimplementations, the vergence of the user's eyes can be tracked and anaccommodation/vergence model can be used to determine the accommodationstate of the user's eyes, which provides information on a renderingplane on which the user is focusing. In some implementations, thewearable system can use cone casting techniques to determine which realor virtual objects are along the direction of the user's head pose oreye pose. Cone casting techniques, described generally, can project aninvisible cone in the direction the user is looking and identify anyobjects that intersect with the cone. The cone castings can involvecasting thin, pencil rays with substantially little transverse width orcasting rays with substantial transverse width (e.g., cones or frustums)from an AR display (of the wearable system) toward physical or virtualobjects. Cone casting with a single ray may also be referred to as raycasting. Detailed examples of cone casting techniques are described inU.S. application Ser. No. 15/473,444, titled “Interactions with 3DVirtual Objects Using Poses and Multiple-DOF Controllers”, filed Mar.29, 2017, the disclosure of which is hereby incorporated by reference inits entirety.

The user interface may be projected by the display system as describedherein (such as the display 220 in FIG. 2). It may also be displayedusing a variety of other techniques such as one or more projectors. Theprojectors may project images onto a physical object such as a canvas ora globe. Interactions with user interface may be tracked using one ormore cameras external to the system or part of the system (such as,e.g., using the inward-facing imaging system 462 or the outward-facingimaging system 464).

FIG. 11 is a process flow diagram of an example of a method 1100 forinteracting with a virtual user interface. The method 1100 may beperformed by the wearable system described herein.

At block 1110, the wearable system may identify a particular UI. Thetype of UI may be predetermined by the user. The wearable system mayidentify that a particular UI needs to be populated based on a userinput (e.g., gesture, visual data, audio data, sensory data, directcommand, etc.). At block 1120, the wearable system may generate data forthe virtual UI. For example, data associated with the confines, generalstructure, shape of the UI etc., may be generated. In addition, thewearable system may determine map coordinates of the user's physicallocation so that the wearable system can display the UI in relation tothe user's physical location. For example, if the UI is body centric,the wearable system may determine the coordinates of the user's physicalstance, head pose, or eye pose such that a ring UI can be displayedaround the user or a planar UI can be displayed on a wall or in front ofthe user. If the UI is hand centric, the map coordinates of the user'shands may be determined. These map points may be derived through datareceived through the FOV cameras, sensory input, or any other type ofcollected data.

At block 1130, the wearable system may send the data to the display fromthe cloud or the data may be sent from a local database to the displaycomponents. At block 1140, the UI is displayed to the user based on thesent data. For example, a light field display can project the virtual UIinto one or both of the user's eyes. Once the virtual UI has beencreated, the wearable system may simply wait for a command from the userto generate more virtual content on the virtual UI at block 1150. Forexample, the UI may be a body centric ring around the user's body. Thewearable system may then wait for the command (a gesture, a head or eyemovement, input from a user input device, etc.), and if it is recognized(block 1160), virtual content associated with the command may bedisplayed to the user (block 1170). As an example, the wearable systemmay wait for user's hand gestures before mixing multiple steam tracks.

Additional examples of wearable systems, UIs, and user experiences (UX)are described in U.S. Patent Publication No. 2015/0016777, which isincorporated by reference herein in its entirety.

Examples Objects in the Field of Regard (FOR) and Field of View (FOV)

FIG. 12A schematically illustrates an example of a field of regard (FOR)1200, a field of view (FOV) of a world camera 1270, a field of view of auser 1250, and a field of fixation of a user 1290. As described withreference to FIG. 4, the FOR 1200 comprises a portion of the environmentaround the user that is capable of being perceived by the user via thewearable system. The FOR may include 4π steradians of solid anglesurrounding the wearable system because the wearer can move his body,head, or eyes to perceive substantially any direction in space. In othercontexts, the wearer's movements may be more constricted, andaccordingly the wearer's FOR may subtend a smaller solid angle.

The field of view of a world camera 1270 can include a portion of theuser's FOR that is currently observed by an outward-facing imagingsystem 464. With reference to FIG. 4, the field of view of a worldcamera 1270 may include the world 470 that is observed by the wearablesystem 400 at a given time. The size of the FOV of the world camera 1270may depend on the optical characteristics of the outward-facing imagingsystem 464. For example, the outward-facing imaging system 464 caninclude a wide angle camera that can image a 190 degree space around theuser. In certain implementations, the FOV of the world camera 1270 maybe larger than or equal to a natural FOV of a user's eyes.

The FOV of a user 1250 can comprise the portion of the FOR 1200 that auser perceives at a given time. The FOV can depend on the size oroptical characteristics of the display of a wearable device. Forexample, an AR/MR display may include optics that provides AR/MRfunctionality when the user looks through a particular portion of thedisplay. The FOV 1250 may correspond to the solid angle that isperceivable by the user when looking through an AR/MR display such as,e.g., the stacked waveguide assembly 480 (FIG. 4) or the planarwaveguide 600 (FIG. 6). In certain embodiments, the FOV of a user 1250may be smaller than the natural FOV of the user's eyes.

The wearable system can also determine a user's field of fixation 1290.The field of fixation 1290 can include a portion of the FOV 1250 atwhich the user's eyes can fixate (e.g., maintain visual gaze at thatportion). The field of fixation 1290 may correspond to the fovea regionof the eyes that a light falls on. The field of fixation 1290 can besmaller than the FOV 1250 of a user, for example, the field of fixationmay be a few degrees to about 5 degrees across. As a result, even thoughthe user can perceive some virtual objects in the FOV 1250 that are notin the field of fixation 1290 but which are in a peripheral field ofview of the user.

FIG. 12B schematically illustrates an example of virtual objects in auser's field of view (FOV) and virtual objects in a field of regard(FOR). In FIG. 12B, the FOR 1200 can contain a group of objects (e.g.1210, 1220, 1230, 1242, and 1244) which can be perceived by the user viathe wearable system. The objects within the user's FOR 1200 may bevirtual and/or physical objects. For example, the user's FOR 1200 mayinclude physical object such as a chair, a sofa, a wall, etc. Thevirtual objects may include operating system objects such as e.g., arecycle bin for deleted files, a terminal for inputting commands, a filemanager for accessing files or directories, an icon, a menu, anapplication for audio or video streaming, a notification from anoperating system, text, a text editing application, a messagingapplication, and so on. The virtual objects may also include objects inan application such as e.g., avatars, virtual objects in games, graphicsor images, etc. Some virtual objects can be both an operating systemobject and an object in an application. In some embodiments, thewearable system can add virtual elements to the existing physicalobjects. For example, the wearable system may add a virtual menuassociated with a television in the room, where the virtual menu maygive the user the option to turn on or change the channels of thetelevision using the wearable system.

A virtual object may be a three-dimensional (3D), two-dimensional (2D),or one-dimensional (1D) object. For example, the virtual object may be a3D coffee mug (which may represent a virtual control for a physicalcoffee maker). The virtual object may also be a 2D graphicalrepresentation of a clock (displaying current time to the user). In someimplementations, one or more virtual objects may be displayed within (orassociated with) another virtual object. A virtual coffee mug may beshown inside of a user interface plane, although the virtual coffee mugappears to be 3D within this 2D planar virtual space.

The objects in the user's FOR can be part of a world map as describedwith reference to FIG. 9. Data associated with objects (e.g. location,semantic information, properties, etc.) can be stored in a variety ofdata structures such as, e.g., arrays, lists, trees, hashes, graphs, andso on. The index of each stored object, wherein applicable, may bedetermined, for example, by the location of the object. For example, thedata structure may index the objects by a single coordinate such as theobject's distance from a fiducial position (e.g., how far to the left orright of the fiducial position, how far from the top or bottom of thefiducial position, or how far depth-wise from the fiducial position).The fiducial position may be determined based on the user's position(such as the position of the user's head). The fiducial position mayalso be determined based on the position of a virtual or physical object(such as a target object) in the user's environment. Accordingly, the 3Dspace in the user's environment may be represented in a 2D userinterface where the virtual objects are arranged in accordance with theobject's distance from the fiducial position.

In FIG. 12B, the FOV 1250 is schematically illustrated by dashed line1252. The user of the wearable system can perceive multiple objects inthe FOV 1250, such as the object 1242, the object 1244, and a portion ofthe object 1230. As the user's pose changes (e.g., head pose or eyepose), the FOV 1250 will correspondingly change, and the objects withinthe FOV 1250 may also change. For example, the map 1210 is initiallyoutside the user's FOV in FIG. 12B. If the user looks toward the map1210, the map 1210 may move into the user's FOV 1250, and (for example),the object 1230 may move outside the user's FOV 1250.

The wearable system may keep track of the objects in the FOR 1200 aswell as the objects in the FOV 1250. For example, the local processing &data module 260 can communicate with the remote processing module 270and remote data repository 280 to retrieve virtual objects in the user'sFOR. The local processing & data module 260 can store the virtualobjects, for example, in a buffer or a temporary storage. The localprocessing & data module 260 can determine a user's FOV using thetechniques descried herein and render a subset of the virtual objectsthat are in the user's FOV. When the user's pose changes, the localprocessing & data module 260 can update the user's FOV and accordinglyrender another set of virtual objects corresponding to the user'scurrent FOV.

Overview of Various User Input Modes

A wearable system can be programmed to accept various modes of inputsfor performing an operation. For example, the wearable system can accepttwo or more of the following types of input modes: voice commands, headposes, body poses (which may be measured, e.g., by an IMU in a belt packor a sensor external to the HMD), eye gazes (also referred to herein aseye pose), hand gestures (or gestures by other body parts), signals froma user input device (e.g., a totem), environmental sensors, etc.Computing devices are typically engineered to generate a given outputbased on a single input from the user. For example, a user can input atext message by typing on a keyboard or guide a movement of a virtualobject using a mouse, which are examples of hand gesture input modes. Asanother example, the computing device can receive a stream of audio datafrom the user's voice and translate the audio data into an executablecommand using voice recognition techniques.

A user input mode may, in some cases, be non-exclusively classified as adirect user input or an indirect user input. The direct user input maybe a user interaction directly supplied by a user, e.g., via avolitional movement of the user's body (e.g., turning the head or eyes,staring at an object or location, saying a phrase, moving a finger orhand). As an example of a direct user input, the user can interact withthe virtual object using a pose such as, e.g., a head pose, an eye pose(also referred to as eye gaze), a hand gesture, or another body pose.For example, the user can look (with head and/or eyes) at a virtualobject. Another example of the direct user input is the user's voice.For example, a user can say “launch a browser” to cause the HMD to opena browser application. As yet another example of the direct user input,the user can actuate a user input device, e.g., via a touch gesture(such as touching a touch-sensitive portion of a totem) or a bodymovement (such as rotating a totem functioning as amulti-degree-of-freedom controller).

In addition or in alternative to direct user input, the user can alsointeract with a virtual object based on an indirect user input. Theindirect user input may be determined from various contextual factors,such as, e.g., a geolocation of the user or the virtual object, anenvironment of the user, etc. For example, the user's geolocation may bein the user's office (rather than the user's home) and different tasks(e.g., work related tasks) can be executed based on the geolocation(e.g., derived from a GPS sensor).

The contextual factor can also include an affordance of the virtualobject. The affordance of the virtual object can comprise a relationbetween the virtual object and the environment of the object whichaffords an opportunity for an action or use associated with the object.The affordances may be determined based on, for example, the function,the orientation, the type, the location, the shape, and/or the size ofthe object. The affordances may also be based on the environment inwhich the virtual object is located. As examples, an affordance of ahorizontal table is that objects can be set onto the table, and anaffordance of a vertical wall is that objects may be hung from orprojected onto the wall. As an example, the may say “place that there”and a virtual office calendar is placed so as to appear horizontal onthe user's desk in the user's office.

A single mode of direct user input may create a variety of limitations,where the number or the type of available user interface operations maybe restricted due to the type of user inputs. For example, the user maynot be able to zoom in or zoom out with head pose because the head posemay not be able to provide precise user interactions. As anotherexample, the user may need to move the thumb back and forth (or move thethumb over a large amount of distance) on a touchpad in order to move avirtual object from the floor to the wall, which may create user fatigueover time.

Some direct input modes, however, may be more convenient and intuitivefor a user to provide. For example, a user can talk to the wearablesystem to issue a voice command without needing to type up the sentenceusing gesture-based keyboard input. As another example, the user can usea hand gesture to point at a target virtual object, rather than moving acursor to identify the target virtual object. While they may not be asconvenient or intuitive, other direct input modes can increase accuracyof the user interaction. For example, a user can move a cursor to thevirtual object to indicate the virtual object is the target object.However, as described above, if a user wants to select the same virtualobject using a direct user input (e.g., a head pose, or other inputsthat are direct results of a user's action), the user may need tocontrol the precise movement of the head, which can cause musclefatigue. A 3D environment (e.g. a VR/AR/MR environment) can addadditional challenges to user interactions because user input will alsoneed to be specified with respect to the depth (as opposed to a planarsurface). This additional depth dimension can create more opportunitiesfor errors than a 2D environment. For example, in 2D environment, a userinput can be translated with respect to a horizontal axis and a verticalaxis in a coordinate system while the user input may need to betranslated with respect to 3 axes (horizontal, vertical, and depth) in a3D environment. Accordingly, an imprecise transaction of a user inputcan cause errors in 3 axes (rather than 2 axes in the 2D environment).

To utilize the existing benefits of direct user inputs while improvingaccuracy of interacting with objects in the 3D space and reducing userfatigue, multiple modes of direct inputs may be used to execute a userinterface operation. The multimodal inputs can further improve existingcomputing devices (in particular a wearable device) for interactionswith virtual objects in a data rich and dynamic environment, such as,e.g., an AR, VR, or MR environment.

In multimodal user input techniques, one or more of the direct inputsmay be used to identify a target virtual object (also referred to as asubject) which a user will interact with and to determine a userinterface operation that will be performed on the target virtual object.For example, the user interface operation may include a commandoperation, such as select, move, zoom, pause, play, and a parameter ofthe command operation (such as, e.g., how to carry out the operation,where or when to the operation will occur, with which object will thetarget object interact, etc.). As an example of identifying a targetvirtual object and determining an interaction to be performed on thetarget virtual object, a user may look at a virtual sticky note (a heador eye pose mode of input), point at a table (a gesture mode of input),and say “move that there” (a voice mode of input). The wearable systemcan identify that the target virtual object in the phrase “move thatthere” is the virtual sticky note (“that”) and can determine the userinterface operation involves moving (the executable command) the virtualsticky note to the table (“there”). In this example, the commandoperation can be to “move” the virtual object, while the parameter ofthe command operation can include a destination object, which is thetable that the user is pointing at. Advantageously, in certainembodiments, the wearable system can increase overall accuracy of a userinterface operation or can increase the convenience of a user'sinteraction by performing a user interface operation based on multiplemodes of direct user inputs (e.g., three modes in the above example,head/eye pose, gesture, and voice). For example, instead of saying “movethe leftmost browser 2.5 feet to the right”, the user can say “move thatthere” (without pointing out the object being moved in the speech input)while using head or hand gestures indicating the object is the leftmostbrowser and use head or hand movements to indicate the distance of themovement.

Examples Interactions in a Virtual Environment Using Various Input Modes

FIG. 13 illustrates examples of interacting with a virtual object usingone mode of user input. In FIG. 13, a user 1310 wears an HMD and isinteracting with virtual content in three scenes 1300 a, 1300 b, and1300 c. The user's head position (and corresponding eye gaze direction)is represented by a geometric cone 1312 a. In this example, the user canperceive the virtual content via the display 220 of HMD. Whileinteracting with the HMD, the user can input a text message via the userinput device 466. In the scene 1300 a, the user's head is at its naturalresting position 1312 a and the user's hands are also at their naturalresting position 1316 a. However, although the user may be morecomfortable typing in the text on the user input device 466, the usercannot see the interface on the user input device 466 to ensure that thecharacter is correctly typed.

In order to see the text entered on the user input device, the user canmove the hands up to position 1316 b as shown in the scene 1300 b.Accordingly, the hands will be in the FOV of the user's head when thehead is at its natural resting position 1312 a. However, the position1316 b is not a natural resting position of the hands, and it may causeuser fatigue as a result. Alternatively, as illustrated in the scene1300 c, the user can move her head to the position 1312 c in order tomaintain the hands at the natural resting position 1316 a. However, themuscles around the user's neck may become fatigued due to the unnaturalposition of the head and the user's FOV is pointed toward the ground orfloor rather than toward the outward world (which may be unsafe if theuser were walking in a crowded area). In either the scene 1300 b or thescene 1300 c, the user's natural ergonomics are sacrificed to meet adesired user interface operation when the user is performing the userinterface operation using a single input mode.

The wearable system described herein can at least partially alleviatethe ergonomic limitations depicted in the scenes 1300 b and 1300 c. Forexample, a virtual interface can be projected within the field of viewof the user in the scene 1300 a. The virtual interface can allow theuser to observe the typed input from a natural position.

The wearable system can also display and support interactions withvirtual content free from device constraints. For example, the wearablesystem can present multiple types of virtual content to a user and auser can interact with one type of content using a touchpad whileinteracting with another type of content using a keyboard.Advantageously, in some embodiments, the wearable system can determinewhich virtual content is a target virtual object (that the user isintended to act upon) by calculating a confidence score (with a higherconfidence score indicative of a higher confidence (or likelihood) thatthe system has identified the correct target virtual object). Detailedexamples on identifying the target virtual object are described withreference to FIGS. 15-18B.

FIG. 14 illustrates examples of selecting a virtual object using acombination of user input modes. In the scene 1400 a, the wearablesystem can present a user 1410 with a plurality of virtual objects,represented by a square 1422, a circle 1424, and a triangle 1426.

The user 1410 can interact with the virtual objects using head pose asillustrated in the scene 1400 b. This is an example of a head pose inputmode. The head pose input mode may involve a cone cast to target orselect virtual objects. For example, the wearable system can cast a cone1430 from a user's head toward the virtual objects. The wearable systemcan detect whether one or more of the virtual objects fall within thevolume of the cone to identify which object the user intends to select.In this example, the cone 1430 intersects with the circle 1424 and thetriangle 1426. Therefore, the wearable system can determine that theuser intends to select either the circle 1424 or the triangle 1426.However, because the cone 1430 intersects with both the circle 1424 andthe triangle 1426, the wearable system may not be able to ascertainwhether the target virtual object is the circle 1424 or the triangle1426 based on the head pose input alone.

In the scene 1400 c, the user 1410 can interact with the virtual objectsby manually orienting a user input device 466, such as totem (e.g., ahandheld remote control device). This is an example of a gesture inputmode. In this scene, the wearable system can determine that either thecircle 1424 or the square 1422 is the intended target because these twoobjects are in the direction at which the user input device 466 ispointing. In this example, the wearable system can determine thedirection of the user input device 466 by detecting a position ororientation of the user input device 466 (e.g., via an IMU in the userinput device 466), or by performing a cone cast originating from theuser input device 466. Because both the circle 1424 and the square 1422are candidates for the target virtual objet, the wearable system cannotascertain which one of them is the object that the user actually wantsto select based solely on the gesture input mode.

In the scene 1400 d, the wearable system can use multimodal user inputsto determine the target virtual object. For example, the wearable systemcan use both the results obtained from the cone cast (head pose inputmode) and from the orientation of the user input device (gesture inputmode) to identify the target virtual object. In this example, the circle1424 is the candidate identified in both the result from the cone castand the result obtained from the user input device. Therefore, thewearable system can determine with high confidence, using these twoinput modes, that the target virtual object is the circle 1424. Asfurther illustrated in the scene 1400 d, the user can give a voicecommand 1442 (illustrated as “Move that”), which is an example of athird input mode (namely, voice), to interact with the target virtualobject. The wearable system can associate the word “that” with thetarget virtual object, the word “Move” with the command to be executed,and can accordingly move the circle 1424. However, the voice command1442 by itself (without indications from the user input device 466 orthe cone cast 143) may cause confusion to the wearable system, becausethe wearable system may not know which object is associated with theword “that”.

Advantageously, in some embodiments, by accepting multiple modes ofinput to identify and interact with a virtual object, the amount ofprecision required for each mode of input may be reduced. For example,the cone cast may not be able to pinpoint an object at a rendering planethat is far away because the diameter of the cone increases as the conegets farther away from the user. As other examples, the user may need tohold the input device at a particular orientation to point toward atarget object and speak with a particular phrase or pace to ensure thecorrect voice input. However, by combining the voice input and theresults from the cone cast (either from a head pose or a gesture usingthe input device), the wearable system can still identify the targetvirtual object without requiring either input (e.g., the cone cast orthe voice input) to be precise. For example, even though the cone castselects multiple objects (e.g., as described with reference to scenes1400 b, 1400 c), the voice input may help narrow down the selection(e.g., increase the confidence score for the selection). For example,the cone cast may capture 3 objects, among which the first object is tothe user's right, the second object is to the user's left, and the thirdobject is in the center of the user's FOV. The user can narrow theselection by saying “select the rightmost object”. As another example,there may be two identically shaped objects in the user's FOV. In orderfor the user to select the correct object, the user may need to givemore descriptions to the object via voice command. For example, ratherthan saying “select the square object”, the user may need to say “selectthe square object that is red”. However, with cone cast, the voicecommand may not have to be as precise. For example, the user can look atone of the square object and say “select the square object” or even“select the object”. The wearable system can automatically select thesquare object that coincides with the user's gaze direction and will notselect the square object that is not in the user's gaze direction.

In some embodiments, the system may have a hierarchy of preferences forcombinations of input modes. For example, a user tends to look in thedirection his or her head is pointing; therefore, eye gaze and head posemay provide information that is similar to each other. A combination ofhead pose and eye gaze may be less preferred, because the combinationdoes not provide much extra information as compared to the use of eyegaze alone or head pose alone. Accordingly, the system may use thehierarchy of modal input preferences to select modal inputs that providecontrasting information rather than generally duplicative information.In some embodiments, the hierarchy is to use head pose and voice as theprimary modal inputs, followed by eye gaze and gesture.

Accordingly, as described further herein, based on multimodal inputs,the system can calculate a confidence score for various objects in theuser's environment that each such object is the target object. Thesystem can select, as the target object, the particular object in theenvironment that has the highest confidence score.

FIG. 15 illustrates an example of interacting with a virtual objectusing a combination of direct user inputs. As depicted in FIG. 15, auser 1510 wears an HMD 1502 configured to display virtual content. TheHMD 1502 may be part of the wearable system 200 described herein and mayinclude a belt-worn power & processing pack 1503. The HMD 1502 may beconfigured to accept user input from a totem 1516. The user 1510 of theHMD 1502 can have a first FOV 1514. The user can observe a virtualobject 1512 in the first FOV 1514.

The user 1510 can interact with the virtual object 1512 based on acombination of direct inputs. For example, the user 1510 can select thevirtual object 1512 through a cone casting technique based on the user'shead or eye pose or by a totem 1516, by a voice command, or by acombination of these (or other) input modes (e.g., as described withreference to FIG. 14).

The user 1510 may shift her head pose to move the selected virtualobject 1512. For example, the user can turn her head leftward to causethe FOV to be updated from the first FOV 1514 to the second FOV 1524 (asshown from the scene 1500 a to the scene 1500 b). The movement of theuser's head can be combined with other direct inputs to cause thevirtual object be moved from the first FOV 1514 to the second FOV 1524.For example, the change in the head pose can be aggregated with otherinputs such as, e.g., a voice command (“move that, to there”), guidancefrom the totem 1516, or an eye gaze direction (e.g., as recorded by theinward-facing imaging system 462 shown in FIG. 4). In this example, theHMD 1502 can use the updated FOV 1524 as a general region that thevirtual object 1512 should be moved into. The HMD 1502 can furtherdetermine the destination of the virtual object's 1512 movement based onthe user's direction of gaze. As another example, the HMD may capture avoice command “move that there”. The HMD can identify the virtual object1512 as the object that the user will interact on (because the user haspreviously selected the virtual object 1512). The HMD can furtherdetermine that the user intends to move the object from the FOV 1514 tothe FOV 1524 by detecting a change of the user's head pose. In thisexample, the virtual object 1512 may initially be in the central portionof the user's first FOV 1514. Based on the voice command and the user'shead pose, the HMD may move the virtual object to the center of theuser's second FOV 1524.

Examples of Identifying a Target Virtual Object or a User InterfaceOperation with Multimodal User Inputs

As described with reference to FIG. 14, in some situations, the wearablesystem may not be able to identify (with sufficient confidence) a targetvirtual object with which the user intends to interact using a singlemode of input. Further, even if multiple modes of user inputs are used,one mode of user input may indicate one virtual object while anothermode of user input may indicate a different virtual object.

To resolve ambiguities and to provide an improved wearable system whichsupports multimodal user inputs, the wearable system can aggregate themodes of user inputs and calculate a confidence score to identify adesired virtual object or user interface operation. As explained above,a higher confidence score indicates a higher probability or likelihoodthat the system has identified the desired target object.

FIG. 16 illustrates an example computing environment for aggregatinginput modes. The example environment 1600 includes three virtualobjects, e.g., associated with the applications A 1672, B 1674, and C1676. As described with reference to FIG. 9, a wearable system caninclude a variety of sensors and can receive a variety of user inputsfrom these sensors and analyze the user inputs to interact with a mixedreality 960. In the example environment 1600, a central runtime server1650 can aggregate direct inputs 1610 and indirect user inputs 1630 toproduce a multimodal interaction for an application. Examples of directinputs 1610 may include a gesture 1612, head pose 1614, voice input1618, totem 1622, direction of eye gaze (e.g., eye gaze tracking 1624),other types of direct inputs 1626, etc. Examples of indirect input 1630may include environment information (e.g., environment tracking 1632),and geolocation 1634. The central runtime server 1650 may include theremote processing module 270. In certain implementations the localprocessing and data module 260 may perform one or more functions of thecentral runtime server 1650. The local processing and data module 260may also communicate with the remote processing module 270 to aggregateinput modes.

A wearable system can track the gesture 1612 using the outward-facingimaging system 464. The wearable system can use a variety of techniquesdescribed in FIG. 9 to track hand gestures. For example, theoutward-facing imaging system 464 can acquire images of the user'shands, and map the images to corresponding hand gestures. Theoutward-facing imaging system 464 may use the FOV camera or a depthcamera (configured for depth detection) to image a user's hand gesture.The central runtime server 1650 can use object recognizer 708 toidentify the user's head gesture. The gesture 1612 can also be trackedby the user input device 466. For example, the user input device 466 mayinclude a touch sensitive surface which can track the user's handmovements, such as, e.g., a swipe gesture or a tap gesture.

An HMD can recognize head poses 1614 using an IMU. A head 1410 may havemultiple degrees of freedom, including three types of rotations (e.g.yaw, pitch, and roll) and three types of translations (e.g., surging,swaying, and heaving). The IMU can be configured, for example, tomeasure 3-DOF movements or 6-DOF movements of the head. The measurementsobtained from the IMU may be communicated to the central runtime server1650 for processing (e.g., to identify a head pose).

The wearable system can use an inward-facing imaging system 462 toperform eye gaze tracking 1624. For example, the inward-facing imagingsystem 462 can include eye cameras configured to obtain images of theuser's eye region. The central runtime server 1650 can analyze theimages (e.g., via the object recognizers 708) to deduce the user'sdirection of gaze or to track the user's eye movements.

The wearable system can also receive inputs from the totem 1622. Asdescribed herein, the totem 1622 can be an embodiment of the user inputdevice 466. Additionally or alternatively, the wearable system canreceive voice input 1618 from a user. The inputs from the totem 1622 andthe voice input 1618 can be communicated to the central runtime server1650. The central runtime server 1650 can use natural languageprocessing in real-time or near real-time for parsing the user's audiodata (for example acquired from the microphone 232). The central runtimeserver 1650 can identify the content of the speech by applying variousspeech recognition algorithms, such as, e.g., hidden Markov models,dynamic time warping (DTW)-based speech recognitions, neural networks,deep learning algorithms such as deep feedforward and recurrent neuralnetworks, end-to-end automatic speech recognitions, machine learningalgorithms (described with reference to FIGS. 7 and 9), semanticanalysis, other algorithms that uses acoustic modeling or languagemodeling, etc. The central runtime server 1650 can also apply voicerecognition algorithms which can identify the identity of the speaker,such as whether the speaker is the user of the wearable device or aperson in the user's background.

The central runtime server 1650 can also receive indirect inputs when auser interacts with the HMD. The HMD can include various environmentalsensors described with reference to FIG. 2. Using data acquired by theenvironmental sensors (along or in combination of data related to thedirect input 1610), the central runtime server 1650 can reconstruct orupdate the user's environment (such as, e.g., the map 920). For example,the central runtime server 1650 can determine the user's ambient lightcondition based on the user's environment. This ambient light conditionmay be used to determine which virtual object the user can interactwith. For example, when a user is in a bright environment, the centralruntime server 1650 may identify the target virtual object to be thevirtual object that supports gestures 1612 as an input mode because thecameras can observe the user's gestures 1612. However, if theenvironment is dark, the central runtime server 1650 may determine thatthe virtual object may be an object that supports voice input 1618rather than gestures 1612.

The central runtime server 1650 can perform the environmental tracking1632 and aggregate direct input modes to produce multimodal interactionfor a plurality of applications. As an example, when a user enters intoa noisy environment from a quiet environment, the central runtime server1650 may disable the voice input 1618. Additional examples on selectingthe modes of inputs based on the environments are further described withreference to FIG. 24.

The central runtime server 1650 can also identify a target virtualobject based on geolocation information of the user. The geolocationinformation 1634 may also be acquired from an environmental sensor (suchas, e.g., a GPS sensor). The central runtime server 1650 may identify avirtual object for potential user interactions where the distancebetween the virtual object and the user is within a threshold distance.Advantageously, in some embodiments, a cone in a cone cast may have alength that is adjustable by the system (e.g., based on number ordensity of objects in the environment). By selecting objects within acertain radius of the user, the number of potential objects that may betarget objects can significantly be reduced. Additional examples ofusing indirect input as a mode of input are described with reference toFIG. 21.

Examples of Ascertaining a Target Object

The central runtime server 1650 can use a variety of techniques todetermine a target object. FIG. 17A illustrates an example ofidentifying a target object using a lattice tree analysis. The centralruntime server 1650 can derive a given value from an input source andproduce a lattice of possible values for candidate virtual objects thata user may potentially interact. In some embodiments, the value can be aconfidence score. A confidence score can include a ranking, a rating, avaluation, quantitative or qualitative values (e.g., a numerical valuein a range from 1 to 10, a percentage or percentile, or a qualitativevalue of “A”, “B”, “C”, and so on), etc. Each candidate object may beassociated with a confidence score, and in some cases, the candidateobject with the highest confidence score (e.g., higher than otherobject's confidence scores or higher than a threshold score) is selectedby the system as the target object. In other cases, objects withconfidence scores below a threshold confidence score are eliminated fromconsideration by the system as the target object, which can improvecomputational efficiency.

In many of the examples herein, a reference is made to selection of atarget virtual object or selection from a group of virtual objects. Thisis intended to illustrate example implementations but is not intended tobe limiting. The techniques described can be applied to virtual objectsor physical objects in the user's environment. For example, the voicecommand “move that there” may be in reference to moving a virtual object(e.g., a virtual calendar) onto a physical object (e.g., the horizontalsurface of the user's desk). Or the voice command “move that there” maybe in reference to moving a virtual object (e.g., a virtual wordprocessing application) to another location within another virtualobject (e.g., another position in the user's virtual desktop).

The context of the command may also provide information as to whetherthe system should attempt to identify virtual objects, physical objects,or both. For example, in the command “move that there”, the system canrecognize that “that” is a virtual object, because the AR/VR/MR systemcannot move an actual, physical object. Accordingly, the system mayeliminate physical objects as candidates for “that”. As described in theexamples above, the target location “there” might be a virtual object(e.g., the user's virtual desktop) or a physical object (e.g., theuser's desk).

Also, the system may assign confidence scores to objects in the user'senvironment, which may be the FOR, FOV, or field of fixation (see, e.g.,FIG. 12A), depending on the context and the goals of the system at thatpoint in time. For example, a user may wish to move a virtual calendarto a position on the user's desk, both of which are in the FOV of theuser. The system may analyze objects within the user's FOV, rather thanall objects in the user's FOR, because the context of the situationsuggests that the command to move the virtual calendar will be to atarget destination in the user's FOV, which may improve processing speedor efficiency. In another case, the user may be reviewing a menu ofmovie selections in a virtual movie application and may be fixating on asmall selection of movies. The system may analyze (and, e.g., provideconfidence scores) for just the movie selections in the user's field offixation (based, e.g., on the user's eye gaze), rather than the full FOV(or FOR), which also may increases processing efficiency or speed.

With reference to the example shown in FIG. 17A, a user can interactwith a virtual environment using two input modes, head pose 1614 and eyegaze 1624. Based on the head pose 1614, the central runtime server 1650can identify two candidate virtual objects associated with application A1672 and application B 1674. The central runtime server 1650 can evenlydistribute a confidence score of 100% between the application A 1672 andthe application B 1674. As a result, the application A 1672 and theapplication B 1674 may each be assigned a confidence score 50%. Thecentral runtime server 1650 can also identify two candidate virtualobjects (application A 1672 and application C 1676) based on thedirection of eye gaze 1624. The central runtime server 1650 can alsodivide a 100% confidence between the application A 1672 and theapplication C 1676.

The central runtime server 1650 may perform a lattice compression logicfunction 1712 to reduce or eliminate outlier confidence values that arenot common among the multiple input modes, or those confidence valuesthat fall below a certain threshold to determine the most likelyapplication that a user intends to interact with. For example, in FIG.17A, the central runtime server 1650 can eliminate application B 1674and application C 1676 because these two virtual objects are notidentified by both the head pose 1614 and the eye gaze 1624 analysis. Asanother example, the central runtime server 1650 can aggregate thevalues assigned to each application. The central runtime server 1650 canset a threshold confidence value to be equal to or above 80%. In thisexample, application A's 1672 aggregated value is 100% (50%+50%);application B's 1674 aggregated value is 50%; and the application C's1676 value is 50%. Because the individual confidence values forapplications B and C are below the threshold confidence value, thecentral runtime server 1650 may be programmed not to select applicationsB and C, but rather to select the application A 1672, becauseapplication A's aggregated confidence value (100%) is greater than thethreshold confidence value.

Although the example in FIG. 17A divides the value (e.g., the confidencescore) associated with an input device equally among candidate virtualobjects, in certain embodiments, the value distribution may not be equalamong candidate virtual objects. For example, if the head pose 1614 hasa value of 10, application A 1672 may receive a value of 7 andapplication B 1674 may receive a value of 3 (because the head pose ispointing more towards A 1672). As another example, if the head pose 1614has a qualitative grade “A”, the application A 1672 may be assignedgrade “A” while application B 1674 and C 1676 do not receive anythingfrom the head pose 1614.

The wearable system (e.g., the central runtime server 1650) can assign afocus indicator to the target virtual object so that the user can morereadily perceive the target virtual object. The focus indicator can be avisual focus indicator. For example, the focus indicator can comprise ahalo (substantially surrounding or near the object), a color, aperceived size or depth change (e.g., causing the target object toappear closer and/or larger when selected), or other visual effectswhich draw the user's attention. The focus indicator can also includeaudible or tactile effects such as vibrations, ring tones, beeps, etc.The focus indicator can provide useful feedback to the user that thesystem is “doing the right thing” by confirming to the user (via thefocus indicator) that the system has correctly determined the objectsassociated with the command (e.g., correctly determined “that” and“there” in a “move that there” command). For example, the identifiedtarget virtual object can be assigned a first focus indicator and thedestination location (e.g., “there” in the command) can be assigned asecond focus indicator. In some cases, if the system has incorrectlydetermined the target object(s), the user may override the system'sdetermination, e.g., by staring (fixating) at the correct object andproviding a voice command such as “no, this not that”.

Examples of Identifying a Target User Interface Operation

In addition to or in alternative to identifying a target virtual object,the central runtime server 1650 can also determine a target userinterface operation based on multiple inputs received. FIG. 17Billustrates an example of determining a target user interface operationbased on multimodal inputs. As depicted, the central runtime server 1650can receive multiple inputs in the form of a head pose 1614 and agesture 1612. The central runtime server 1650 can display multiplevirtual objects associated with, e.g., application A 1672 andapplication B 1674, to a user. The head pose input mode by itself,however, may be insufficient to determine the desired user interfaceactions because there is a 50% confidence that the head pose applies toa user interface operation (shown as modification options 1772)associated with the application A 1672 and there is another 50%confidence that the head pose applies to another user interfaceoperation (shown as modification options 1774) associated with theapplication B 1674.

In various embodiments, a particular application or a type of userinterface operations may be programmed to be more responsive to acertain mode of input. For example, the HTML tags or JavaScriptprogramming of the application B 1674 may be set to be more responsiveto a gesture input more than that of the application A 1672. Forexample, the application A 1672 may be more responsive to a head pose1672 than a gesture 1612, while a “select” operation may be moreresponsive to the gesture 1612 (e.g., a tap gesture) than the head pose1614, because a user may be more likely to use a gesture to select anobject than a head pose in some cases.

With reference to FIG. 17B, the gesture 1612 may be more responsive to acertain type of user interface operation in the application B 1674. Asillustrated, the gesture 1612 may have a higher confidence associatedwith user interface operations for application B while the gesture 1612may not be applicable for interface operations in the application A1672. Accordingly, if the target virtual object is the application A1672, the input received from the head pose 1614 may be the target userinterface operation. But if the target virtual object is the applicationB 1674, then the input received from the gesture 1612 (alone or incombination with the input based on the head pose 1614) may be thetarget user interface operation.

As another example, because the gesture 1612 has a higher confidencelevel than the head pose 1614 when the user is interacting with theapplication B, the gesture 1612 may become the primary input mode forapplication B 1674 while the head pose 1614 may be the secondary inputmode. Accordingly, the input received from the gesture 1612 may beassociated with a higher weight than the head pose 1614. For example, ifthe head pose indicates that a virtual object associated with theapplication B 1674 should stay still while the gesture 1612 indicatesthat the virtual object should be moved leftward, the central runtimeserver 1650 may render the virtual object moving leftward. In certainimplementations, a wearable system can allow a user to interact with avirtual object using the primary input mode and can consider thesecondary input mode if the primary input mode is insufficient todetermine the user's action. For example, the user can interact with theapplication B 1674 with mostly gestures 1612. However, when the HMDcannot determine a target user interface operation (because e.g., theremay be multiple candidate virtual objects in the application B 1674 orif the gesture 1612 is unclear), the HMD can use head pose as an inputto ascertain the target virtual object or a target user interfaceoperation to be performed on the application B 1674.

The score associated with each input mode may be aggregated to determinea desired user interface operation. FIG. 17C illustrates an example ofaggregating confidence scores associated with input modes for a virtualobject. As illustrated in this example, a head pose input 1614 producesa higher confidence score for application A (80% confidence) overapplication B (30% confidence), whereas the gesture input 1612 producesa higher confidence score for application B (60% confidence) overapplication A (30% confidence). The central runtime server 1650 canaggregate the confidence scores for each objects based on the confidencescores derived from each user input mode. For example, the centralruntime server 1650 can produce an aggregate score of 110 forapplication A 1672 and an aggregate score of 90 for application B 1674.The aggregated scores may be weighted or unweighted averages or othermathematical combinations. Because the application A 1672 has a higheraggregate score than Application B 1674, the central runtime server 1650may select application A as the application to be interacted with.Additionally or alternatively, due to the higher aggregation score ofthe application A 1672, the central runtime server 1650 can determinethat the head pose 1614 and the gesture 1612 are intended to perform anuser interface operation on the application A 1672, even though theapplication B is more “responsive” to the gesture 1612 than applicationA.

In this example, the central runtime server 1650 aggregates theconfidence scores occurred by adding the confidence scores of variousinputs for a given object. In various other embodiments, the centralruntime server 1650 can aggregate the confidence scores using techniquesother than a simple addition. For example, an input mode or a score maybe associated with a weight. As a result, the aggregation of confidencescores will take into account the weight assigned to the input mode orthe score. The weights may be user adjustable to permit the user toselectively adjust the “responsiveness” of the multimodal interactionwith the HMD. The weights may also be contextual. For example, weightsused in a public place may emphasize head or eye pose over handgestures, to avoid possible social awkwardness of having the userfrequently gesture while operating the HMD. As another example, in asubway, airplane, or train, voice commands may be given less weight thanhead or eye poses, since a user may not wish to speak out loud to his orher HMD in such an environment. Environmental sensors (e.g., GPS) mayassist in determining the appropriate context for where the user isoperating the HMD.

Although the examples in FIGS. 17A-17C are illustrated with reference totwo objects, the techniques described herein can also be applied whenthere are more or fewer objects. In addition, techniques described withreference to these figures can be applied to applications of a wearablesystem or virtual objects associated with one or more applications.Furthermore, the techniques described herein can also be applied todirect or indirect input modes, other than head pose, eye gaze, orgestures. For example, the voice command may also be used. In addition,despite the central runtime server 1650 having been used as an examplethroughout to describe the processing of the various input modes, thelocal processing & data module 260 of the HMD may also perform a portionor all of the operations in addition to or in alterative to the centralruntime server 1650.

Example Techniques for Calculating a Confidence Score

The wearable system can use one or a combination of a variety oftechniques to calculate a confidence score of an object. FIGS. 18A and18B illustrate examples of calculating confidence scores for objectswithin a user's FOV. The user's FOV may be calculated based on theuser's head pose or eye gaze, for example, during a cone cast. Theconfidence scores in the FIGS. 18A and 18B may be based on a singleinput mode (such as e.g., the user's head pose). Multiple confidencescores can be calculated (for some or all of the various multimodalinputs) and then aggregated to determine a user interface operation or atarget virtual object based on multimodal user inputs.

FIG. 18A illustrates an example where the confidence score of a virtualobject is calculated based on the portion of the virtual object thatfalls within the user's FOV 1810. In FIG. 18A, the user's FOV has aportion of two virtual objects (represented by a circle 1802 and atriangle 1804). The wearable system can assign confidence scores to thecircle and the triangle based on the proportion of the projected area ofthe object that falls within the FOV 1810. As illustrated, approximatelyhalf of the circle 1802 falls within the FOV 1810, and as a result, thewearable system may assign a confidence score of 50% to the circle 1802.As another example, about 75% of the triangle is within the FOV 1810,Therefore, the wearable system may assign a confidence score of 75% tothe triangle 1804.

The wearable system can use regression analysis of content in the FOVand FOR to calculate the proportion of a virtual object within a FOV. Asdescribed with reference to FIG. 12B, although the wearable system keepstrack of the objects in the FOR, the wearable system may deliver theobjects (or portions of the objects) that are in the FOV to a renderingprojector (e.g., the display 220) for display within the FOV. Thewearable system can determine which portions are provided for therendering projector and analyze the proportion that is delivered to therendering projector against the virtual object as a whole to determinethe percentage of the virtual object that is within the FOV.

In addition to or as an alternative to calculating a confidence scorebased on the proportional area that falls within the FOV, the wearablesystem can also analyze the space near the object in the FOV todetermine a confidence score of the object. FIG. 18B illustrates anexample of calculating a confidence score based on the evenness of spacesurrounding a virtual object in the FOV 1820. The FOV 1820 includes twovirtual objects as depicted by the triangle 1814 and the circle 1812.The space around each virtual object may be represented by vectors. Forexample, the space around the virtual object 1812 may be represented byvectors 1822 a, 1822 b, 1822 c, and 1822 d, while the space around thevirtual object 1814 may be represented by vectors 1824 a, 1824 b, 1824c, and 1824 d. The vectors may originate from a virtual object (or aboundary to the virtual object) and end at the edge of the FOV 1820. Thesystem can analyze the distribution of the lengths of the vectors fromthe objects to the edge of the FOV to determine which of the objects ispositioned more towards the center of the FOV. For example, an object atthe very center of a circular FOV would have a relatively uniformdistribution of vector lengths, whereas an object very close to an edgewould have a non-uniform distribution of vector lengths (since somevectors pointing to the nearby edge would be shorter but vectorspointing to the most distant edge would be longer). As depicted in FIG.18B, the distribution of lengths of the vectors from the virtualtriangle 1814 to the edges of field of view 1820 vary more than thedistribution of lengths of the vectors from circle 1812 to the edges offield of view 1820, which indicates the virtual circle 1812 is moretowards the center of the FOV 1820 than the virtual triangle 1814. Thevariability of the distribution of the vector lengths may be representedby a standard deviation or variance (or other statistical measure) ofthe lengths. The wearable system can accordingly assign a higherconfidence score to the virtual circle 1812 over the virtual triangle1814.

Besides the techniques described with reference to FIGS. 18A and 18B,the wearable system can assign confidence score to a virtual objectbased on historical analysis of the user's interactions. As an example,the wearable system can assign a higher confidence score to a virtualobject with which the user frequently interacts. As another example, oneuser may tend to move virtual objects using voice commands (e.g., “movethat there”), whereas another user may prefer to use hand gestures(e.g., by reaching out and “grabbing” a virtual object and moving it toanother position). The system can determine such user tendencies fromthe historical analysis. As yet another example, an input mode may befrequently associated with a particular user interface operation or aparticular virtual object, as a result, the wearable system may increasethe confidence score to the particular user interface operation or theparticular virtual object, even though there may be an alternative userinterface operation or virtual object based on the same input.

Given either field of view 1810 or 1820 as depicted in FIG. 18A or 18B,a second input mode can facilitate the selection of the appropriatevirtual object or an appropriate user interface operation in the virtualobject. For example, a user can say “enlarge the triangle” to increasethe size of the triangle within field of view 1810. As another example,in FIG. 18A, a user may give a voice command, such as “make that twiceas big”. The wearable system may determine that the subject (e.g., thetarget object) of the voice command is the virtual object 1804 becausethe virtual object 1804 has a higher confidence score based on the headpose. Advantageously, in some embodiments this reduces the specificityof interaction needed to produce the desired result. For example, theuser don't have to say “make the triangle twice as big” in order for thewearable system to achieve the same interaction.

The triangles and circles in FIGS. 18A and 18B are for illustrationpurposes only. Various techniques described herein can also be appliedto virtual content that supports more complex user interactions.

Example Multimodal Interactions in a Physical Environment

In addition to or in alternative to interacting with virtual objects,the wearable system can also offer a broad range of interactions withina real world environment. FIGS. 19A and 19B illustrate examples ofinteracting with a physical environment using multimodal inputs. In FIG.19A, 3 modes of inputs are illustrated: hand gestures 1960, head pose1920, and inputs from the user input device 1940. The head pose 1920 canbe determined using pose sensors. The pose sensors may be an IMU,gyroscopes, magnetometers, accelerometers, or other types of sensorsdescribed in FIG. 2. The hand gesture 1960 may be measured using anoutward-facing imaging system 464 while the user input device 1940 maybe an embodiment of the user input device 466 shown in FIG. 4.

In some embodiments, the wearable system can also measure the user's eyegaze. The eye gaze may include a vector extending from each of theuser's eyes to a position where the two eyes' lines of sight converge.The vector can be used to determine the direction a user is looking andcan be used to select or identify virtual content at the convergencepoint or along the vector. Such eye gaze may be determined byeye-tracking techniques such as, e.g., glint detection, iris or pupilshape mapping, infrared illumination, or binocular eye imaging withregression of an intersection point originating from a respective pupilorientation. Eye gaze or head pose may then be considered a source pointfor a cone cast or ray cast for virtual object selection.

As described herein, an interaction event to move selected virtualcontent within a user's environment (for example, “put that there”) mayrequire determination of a command operation (e.g., “put”), a subject(e.g., “that” as may be determined from the above multimodal selectiontechniques), and a parameter (e.g., “there”). The command operation (orcommand for short) and the subject (which is also referred to as thetarget object or the target virtual object) may be determined using acombination of input modes. For example, a command to move the subject1912 may be based on a head pose 1920 change (e.g., head turning ornodding) or a hand gesture 1960 (e.g. a swipe gesture), alone or incombination. As another example, the subject 1912, may be determinedbased on a combination of head pose and eye gaze. Accordingly, thecommand based on multimodal user inputs can also sometimes be referredto as a multimodal input command.

The parameter may also be determined using a single input or amultimodal input. The parameter may be associated with objects in theuser's physical environment (e.g., a table or a wall) or objects in theuser's virtual environment (e.g., a movie application, an avatar or avirtual building in a game). Identifying a real world parameter canallow for a quicker and more accurate content placement response in someembodiments. For example, a particular virtual object (or a portion ofthe virtual object) may be substantially planar with a horizontalorientation (e.g., the normal of the virtual object is perpendicular toa floor of a room). When a user initiates an interaction of moving thevirtual object, the wearable system can identify a real world surfacewith a similar orientation (e.g., a tabletop) and move the virtualobject to the real world surface. In certain embodiments, such movementsmay be automatic. For example, the user may want to move a virtual bookfrom where it is sitting on a floor. The only available horizontalsurface in the room may be the user's study desk. Accordingly, thewearable system can automatically move the virtual book to the surfaceof the study desk in response to a voice command of “move that” withoutthe user inputting additional commands or parameters, because thesurface of the desk is the most likely location for where the user wouldwant to move the book. As another example, the wearable system canidentify real world surfaces of a suitable size for given content andthereby may provide better parameter matching for a user. For example,if a user is watching a virtual video screen with a given display sizeand desires to move it to a particular surface with a simple voicecommand, the system may determine which real world surfaces provide thenecessary surface area to best support the virtual video's display size.

The wearable system can identify a target parameter (e.g., a targetsurface) using the techniques described with reference to identifying atarget virtual object. For example, the wearable system can calculate aconfidence score associated with a plurality of target parameters basedon indirect user inputs or direct user inputs. As an example, thewearable system can calculate a confidence score associated with a wallbased on direct input (such as the user's head pose) and indirect input(such as the characteristics of the wall (e.g., a vertical surface)).

Example Techniques of Identifying Real World Parameters

The wearable system can use a variety of techniques to determine aparameter (such as a target location) of a multimodal input command. Forexample, the wearable system can use various depth sensing techniques,such as, e.g., applying the SLAM protocol to environmental depthinformation (e.g., described with reference to FIG. 9), or constructionor access of a mesh model of the environment. In some embodiments, depthsensing determines the distance between known points in a 3D space(e.g., the distance between sensors on an HMD) and a point of interest(“POI”) on a surface of an object in the real world (e.g., a wall forlocating virtual content). This depth information may be stored in theworld map 920. A parameter for the interaction may be determined based acollection of POIs.

The wearable system can apply these depth sensing techniques to dataobtained from depth sensors to determine the metes and bounds of aphysical environment. The depth sensors may be part of theoutward-facing imaging system 464. In some embodiments, depth sensorsare coupled to IMUs. The data acquired from the depth sensors can beused to determine orientation of a plurality of POIs relative to oneanother. For example, the wearable system can compute a truncated signeddistance function (“TSDF”) for the POIs. A TSDF can include a numericalvalue for each POI. The numerical value may be zero when a point iswithin a given tolerance of a particular plane, positive when a point isspaced away from the particular plane in a first direction (e.g., aboveor outside), and negative when the point is spaced away from theparticular plane in a second (e.g., opposite) direction (e.g., below orinside). The computed TSDF can be used to define a 3-D volumetric gridof bricks or boxes along orientations as determined by the IMU, whichare aligned in, above, and below the particular plane to construct orrepresenting a particular surface.

POIs outside of a given planar tolerance (e.g., with absolute value ofTSDF greater than the tolerance) may be eliminated, leaving only aplurality of POIs adjacent to one another within given tolerance, tocreate virtual representations of surfaces within the real worldenvironment. For example, the real world environment may include aconference table. There may be various other objects (e.g., telephones,laptop computers, coffee mugs, etc.) on top of the conference table. Forthe surfaces of the conference table, the wearable system can keep POIsassociated with the conference table and remove the POIs for the otherobjects. As a result, a planar map (delineating the surfaces of theconference table) can represent the conference table with only thepoints that belong to the conference table. The map can leave out thepoints associated with the objects on top of the conference table. Incertain embodiments, the collection of POIs remaining in the planar mapmay be referred to as “workable surfaces” of the environment, becausethese regions of the planar map represent space(s) where virtual objectsmay be placed. For example, when a user wants to move a virtual screento a table, the wearable system can identify suitable surfaces (such astable tops, walls, etc.) in the user's environment while eliminating theobjects (e.g., a coffee mug or a pencil or a wall painting) or surfaces(e.g., a surface of a bookshelf) that are not suited for placing thescreen. In this example, the identified suitable surfaces may be theworkable surfaces of the environment.

Referring back to the example shown in FIG. 19A, the environment 1900can include a physical wall 1950. An HMD or the user input device 1940can house a depth sensor system (such as, e.g., a time of flight sensoror vertical cavity surface emitting laser (VCSEL)) and pose sensors(such as, e.g., IMUs). The data obtained by the depth sensor system canbe used to identify various POIs in the user's environment. The wearablesystem can group POIs that are substantially planar together to form aboundary polygon 1910. The boundary polygon 1910 may be an exampleembodiment of a workable surface.

In some embodiments, the outward-facing imaging system 464 can identifya user gesture 1960 which may include a finger pointing to a regionwithin the real world environment 1900. The outward-facing imagingsystem 464 can identify a pre-measured boundary polygon 1910 bydetermining a sparse point vector construction of the finger pointingtowards boundary polygon 1910.

As illustrated in FIG. 19A, there can be a virtual video screen 1930inside of the boundary polygon 1910. The user can interact within thevirtual object 1912 inside of the virtual video screen 1930 usingmultimodal input. FIG. 19B depicts an interaction using multimodal inputof virtual content in a real world environment. The environment in FIG.19B includes a vertical surface 1915 (which may be part of a wall) and asurface 1917 on a table top. In a first state 1970 a, the virtualcontent 1926 is initially displayed within the boundary polygon 1972 aon the wall surface 1915. The user can select the virtual object 1926,for example, through a cone cast or a multimodal input (including two ormore of the gesture 1960, head pose 1920, eye gaze, or an input from theuser input device 1940).

The user can use another input as part of the multimodal input to selectthe surface 1917 as a destination. For example, the user can use a headpose combined with a hand gesture to indicate that the surface 1917 isthe destination. The wearable system can recognize the surface 1917 (andthe polygon 1972 b) by grouping POIs that appear to be on the sameplane. The wearable system can also use other surface recognitiontechniques to identify the surface 1917.

The user can also use a multimodal input to transfer the virtual content1126 to boundary polygon 1972 b on the surface 1917 as illustrated inthe second state 1970 b. For example, the user can move the virtualcontent 1926 through a combination of changes in head pose and amovement of the user input device 1940.

As another example, the user could say “move that there” via themicrophone 232 of the wearable system which can receive the audio streamand parse this command from it (as described herein). The user cancombine this voice command with a head pose, eye gaze, gesture, or anactuation of the totem. The wearable system can detect the virtualobject 1926 as the subject of this command because the virtual object1926 is the highest confidence object (see, e.g., the dashed lines inscene 1970 a indicating the user's finger 1960, HMD 1920 and totem 1940are oriented toward the object 1926). The wearable system can alsoidentify the command operation as “move” and determine the parameter ofthe command to be “there”. The wearable system can further determinethat “there” refers to boundary polygon 1972 b based on input modesother than the voice (e.g., eye gaze, head pose, gesture, totem).

A command in an interaction event can involve adjustments andcalculations of multiple parameters. For example, the parameters mayinclude a destination, a placement, an orientation, an appearance (e.g.,size or shape), or an animation of a virtual object. The wearable systemcan automatically calculate a parameter even though the direct input isnot explicit in changing the parameter. As an example, the wearablesystem can automatically change the orientation of the virtual object1926 when it is moved from a vertical surface 1915 to a horizontalsurface 1917. In the first state 1970 a, the virtual content 1926 is asubstantially vertical orientation on the surface 1915. When the virtualcontent 1926 is moved to the surface 1917 in the second state 1970 b,the orientation of the virtual content 1926 may be kept consistent(e.g., maintaining the vertical orientation) as shown by the virtualobject 1924. The wearable system can also automatically adjust theorientation of the virtual content 1926 to align with the orientation ofthe surface 1917 such that the virtual content 1926 appears to be in ahorizontal position as illustrated by the virtual object 1922. In thisexample, the orientation may be automatically adjusted based onenvironment tracking 1632 as an indirect input. The wearable system canautomatically consider the object's (e.g., the surface 1917)characteristics when the wearable system determines that the object isthe target destination object. The wearable system can adjust theparameters of the virtual object based on the characteristics of thetarget destination object. In this example, the wearable systemautomatically rotated the orientation of the virtual object 1926 basedon the orientation of the surface 1917.

Additional examples of automatically placing or moving virtual objectsare described in U.S. application Ser. No. 15/673,135, filed Aug. 9,2017, titled “AUTOMATIC PLACEMENT OF A VIRTUAL OBJECT IN ATHREE-DIMENSIONAL SPACE,” the disclosure of which is hereby incorporatedby reference herein in its entirety.

In certain implementations, an input may explicitly modify multipleparameters. A voice command of “place that there flat” may alter theorientation of the virtual object 1926 in addition to identifying thesurface 1917 as the destination. In this example, both the word “flat”and the word “there” can be parameter values, where “there” causes thewearable system to update the location of the target virtual objectwhereas the word “flat” is associated with the orientation of the targetvirtual object at the destination location. To execute the parameter“flat”, the wearable system can match the orientation of the virtualobject 1926 to match the orientation of the surface 1917.

In addition to or as an alternative to selecting and moving a virtualobject, a multimodal input can interact with virtual content in otherways. FIG. 20 illustrates an example of automatically resizing a virtualobject based on multimodal inputs. In FIG. 20, the user 1510 can wear anHMD 1502 and can interact with virtual objects using hand gestures andvoice commands 2024. FIG. 20 illustrates four scenes 2000 a, 2000 b,2000 c, and 2000 d. Each scene includes a display screen and a virtualobject (illustrated by the smiley face).

In the scene 2000 a, the display screen has a size 2010 and the virtualobject has a size 2030. The user can change the hand gesture from thegesture 2020 to the gesture 2022 to indicate that the user wants toadjust the size of either the virtual object or the display screen. Theuser can use voice input 2024 to indicate whether the virtual object orthe display screen is the subject of manipulation.

As an example, the user may want to enlarge both the display screen andthe virtual object. Accordingly, the user can use the input gesture 2022as a command to enlarge. The parameter for the degree of expansion maybe expressed by the extent of the outstretched figures. In the meantime,the user can use the voice input 2024 to dictate the subject of theinteraction. As shown in the scene 2000 b, the user may say “all” toproduce an enlarged display 2012 and an enlarged virtual object 2032. Asanother example, in the scene 2000 c, the user may say “content” toproduce an enlarged virtual object 2034 while the size the displayscreen remains the same as that in the scene 2000 a. As yet anotherexample, in the scene 2000 d, the user can say “display” to produce anenlarged display screen 2016, while the virtual object remains the samesize as that in the scene 2000 a.

Examples of Indirect Input as an Input Mode

As described herein, a wearable system can be programmed to allow userinteractions with direct user inputs and indirect user inputs as part ofthe multimodal inputs. The direct user inputs may include head pose, eyegaze, voice input, gesture, inputs from a user input device, or otherinputs that directly from a user. Indirect inputs may include variousenvironment factors, such as, e.g., user's position, user'scharacteristics/preferences, object's characteristics, characteristicsof the user's environment, etc.

As described with reference to FIG. 2, the wearable system can include alocation sensor, such as, e.g., a GPS or radar or lidar. The wearablesystem can determine a subject of user's interactions as a function ofthe object's proximity to the user. FIG. 21 illustrates an example ofidentifying a target virtual object based on objects' locations. FIG. 21schematically illustrates a bird's eye view 2100 of the user's FOR. TheFOR can include a plurality of virtual objects 2110 a-2110 q. The usercan wear an HMD which can include a location sensor. The wearable systemcan determine candidate target objects based on the objects' proximityto the user. For example, the wearable system can select virtual objectswithin a threshold radius (e.g., 1 m, 2 m, 3 m, 5 m, 10 m, or more) fromthe user as candidate target virtual objects. In FIG. 21, the virtualobjects (e.g., virtual objects 2110 o, 2110 p, 2110 q) fall within thethreshold radius (illustrated by the dashed circle 2122) from the user'sposition 2120. As a result, the wearable system can set virtual objects2110 o-2110 q as candidate target virtual objects. The wearable systemcan further refine the selections based on other inputs (such as e.g.,the user's head pose). The threshold radius can depend on contextualfactors such as the location of the user. For example, the thresholdradius may be shorter if the user is in his or her office than if theuser is outside in a park. The candidate objects can be selected from aportion of the region 2122 within the threshold radius from the user.For example, only those objects that are both within the circle 2122 andin the user's FOV (e.g., generally in front of the user) may becandidates, while objects within the circle 2122 but outside the user'sFOV (e.g., behind the user) may not be candidates. As another examplemultiple virtual objects may be along a common line of sight. Forexample, a cone cast may select multiple virtual objects. The wearablesystem can use the user's position as another input to determine atarget virtual object or a parameter for user interaction. For example,cone cast may select objects corresponding to different depth planes,but the wearable system may be configured to identify a target virtualobject as an object within the user's hand's reach.

Similar to direct input, an indirect input may also be assigned to avalue which can be used for calculating the confidence scores of avirtual object. For example, while multiple subjects or parameters werewithin a common confidence of selection, the indirect input couldfurther be used as a confidence factor. With reference to FIG. 21, thevirtual objects within the circle 2122 may have a higher confidencescore than the virtual objects in-between the circle 2122 and the circle2124 because the objects that are closer to the user's position 2120 aremore likely to be the objects that the user is interested in interactingwith.

In the example shown in FIG. 21, dashed circles 2122, 2124 areillustrated for convenience, representing the projection of a sphere ofcorresponding radius onto the plane shown in FIG. 21. This is forillustration and is not limiting; in other implementations, other shapedregions (e.g., polyhedral) may be chosen.

FIGS. 22A and 22B illustrate another example of interacting with auser's environment based on a combination of direct and indirect inputs.These two figures show two virtual objects, virtual object A 2212 andvirtual object B 2214 in the FOV 1270 of a world camera which may belarger than the FOV 1250 of the user. The virtual object A 2212 is alsowithin the FOV 1250 of the user. For example, the virtual object A 2212may be a virtual document that the user is currently viewing while thevirtual object B 2214 may be a virtual sticky note on a wall. However,while the user is interacting with virtual object A 2212, the user maywant to look at the virtual object B 2214 to obtain additionalinformation from the virtual object B 2214. As a result, the user mayturn the head rightward (to change the FOV 1250) in order to view thevirtual object B 2214. Advantageously, in some embodiments, rather thanturning the head, the wearable system may detect a change in the user'sdirection of gaze (toward the direction of the virtual object B 2214),and as a result, the wearable system can automatically move the virtualobject B 2214 within the user's FOV without needing the user to changehis head pose. The virtual object B may overlay the virtual object A (orbe included within the object A) or the object B may be placed withinthe user FOV 1250 but spaced at least partially apart from object A (sothat object A is also at least partly visible to the user).

As another example, the virtual object B 2214 may be on another userinterface screen. The user may want to switch in-between the userinterface screen having the virtual object A 2212 and the user interfacescreen having the virtual object B 2214. The wearable system can makethe switch without changing the user's FOV 1250. For example, upondetection of a change in eye gaze or an actuation of the user inputdevice, the wearable system can automatically move the user interfacescreen having the virtual object A 2212 to be outside of the user's FOV1250 while move the user interface screen having the virtual object B2214 to be inside of the user's FOV 1250. As another example, thewearable system can automatically overlay the user interface screenhaving the virtual object B 2214 on top of the user interface screenhaving the virtual object A 2212. Once the user provides an indicationthat he has finished with a virtual user interface screen, the wearablesystem can automatically move the virtual user interface screen outsideof the FOV 1250.

Advantageously, in some embodiments, the wearable system can identifythe virtual object B 2214 as the target virtual object to be movedinside of the FOV based on multimodal inputs. For example, the wearablesystem can make the determination based on the user's eye gaze andpositions of the virtual objects. The wearable system can set the targetvirtual object as an object that's on the user's direction of gaze andis the closet object to the user.

Example Processes of Interacting with a Virtual Object Using MultimodalUser Inputs

FIG. 23 illustrates an example process of interacting with a virtualobject using multimodal inputs. The process 2300 can be executed by thewearable system described herein. For example, the process 2300 may beexecuted by the local processing & data module 260, remote processingmodule 270, and the central runtime server 1650, alone or incombination.

At block 2310, the wearable system can optionally detect an initiationcondition. The initiation can be a user-initiated input which canprovide an indication that the user intends to issue a command to thewearable system. The initiation condition may be predefined by thewearable system. The initiation condition may be a single input or acombination input. For example, the initiation condition may be a voiceinput, such as, e.g., by saying the phrase “Hey, Magic Leap”. Theinitiation condition can also be gesture based. For example, thewearable system can detect the presence of an initiation condition whena user's hand is detected within the FOV of the world camera (or the FOVof the user). As another example, the initiation condition may be aspecific hand motion, such as, e.g., a snap of the fingers. Theinitiation condition can also be detected when a user actuates a userinput device. For example, a user can click on a button on a user inputdevice indicating that the user will issue a command. In certainimplementations, the initiation condition may be based on multimodalinputs. For example, both a voice command and a hand gesture may berequired for the wearable system to detect the presence of theinitiation condition.

The block 2310 is optional. In some embodiments, the wearable system mayreceive and start parsing multimodal inputs without the detection of theinitiation condition. For example, when a user is watching a video, thewearable system may intake the user's multimodal inputs to adjust thevolume, fast forward, rewind, skip to the next episode, etc., withoutrequiring the user to first provide the initiation condition.Advantageously, in some embodiments, the user may not need to wake upthe video screen (e.g., so that the video screen can present the timeadjustment or volume adjustment tools) before the user can interact withthe video screen using multimodal inputs.

At block 2320, the wearable system can receive multimodal inputs for auser interaction. The multimodal inputs may be direct or indirectinputs. Example input modes may include voice, head pose, eye gaze,gesture (on a user input device or in the air), inputs on a user inputdevice (such as, e.g., a totem), user's environment, or characteristicsof objects (physical or virtual objects) in the 3D space.

At block 2330, the wearable system can parse the multimodal inputs toidentify a subject, a command, and a parameter of the user interaction.For example, the wearable system can assign confidence scores tocandidate target virtual objects, target commands, and target parametersand select the subject, command, and parameters based on the highestconfidence scores. In some embodiments, one input mode may be theprimary input mode while another input mode may be the secondary inputmode. The inputs from the secondary input mode may supplement the inputfrom the primary input mode to ascertain a target subject, command, orparameter. For example, the wearable system may set the head pose as theprimary input mode and set the voice command as the secondary inputmode. The wearable system can first interpret the inputs from primaryinput mode as much as possible and then interpret the additional inputsfrom the secondary input mode. If the additional input is interpreted tosuggest a different interaction from the inputs of the primary input,the wearable system can automatically provide a disambiguation prompt tothe user. The disambiguation prompt may request the user to select thedesired task from: the interpretation of the primary input oralternative options based on the interpretation of the secondary input.Although this example is described with reference to a primary inputmode and a second input mode, in various situations, there may be morethan two input modes. The same technique can also be applicable on athird input mode, a fourth input mode, and so forth.

At block 2340, the wearable system can execute the user interactionbased on the subject, command, and the parameter. For example, themultimodal inputs may include an eye gaze and a voice command “put thatthere”. The wearable system can determine that the subject of theinteraction is the object that the user is currently interacting with,the command is “put”, and the parameter is the center of the user'sfield of fixation (determined based on the user's eye gaze direction).Accordingly, the user can move the virtual object that the user iscurrently interacting with to the center of the user's field offixation.

Examples of Setting Direct Input Modes Associated with a UserInteraction

In some situations, such as when the user is interacting with a wearablesystem using poses, gestures, or voices, there is a risk that otherpeople near the user could “hijack” the user's interaction by issuing acommand using these direct inputs. For example, a user A could standnear a user B in a park. The user A can interact with an HMD using voicecommands. The user B can hijack the user A's experience by saying “takea picture”. This voice command issued by user B can cause the user A'sHMD to take a picture even though user A never intended to take apicture. As another example, user B could perform a gesture within theFOV of a world camera of the user A's HMD. This gesture can cause theuser A's HMD to go to a home page, for example, while the user A isplaying a video game.

In some implementations, the input can be analyzed to determine if theinput originated from the user. For example, the system can applyspeaker recognition techniques to determine whether the command “take apicture” was said by the user A or the hijacker B. The system may applycomputer vision techniques to determine whether the gesture was made byuser A's hand or by the hijacker B's hand.

Additionally or alternatively, to prevent security breaches andinterruptions of a user's interactions with the wearable system, thewearable system can automatically set available direct input modes basedon indirect inputs or require multiple modes of direct inputs before acommand is issued. FIG. 24 illustrates an example of setting directinput modes associated with a user interaction. Three direct inputs:voice 2412, head pose 2414, and hand gestures 2416 are illustrated inFIG. 24. As described further below, the slider bars 2422, 2424, and2426 represent an amount by which each input is weighted in determininga command. If the slider is all the way toward the right, the input isgiven full weight (e.g., 100%), if the slider is all the way to theleft, the input is given zero weight (e.g., 0%), and if the slider is inbetween these extreme settings, the input is given partial weight (e.g.,20% or 80% or some other value intermediate values, such as a valuebetween 0 and 1). In this example, the wearable system can be set torequire both voice commands 2422 and hand gestures 2426 (while not usinghead pose 2414) before a command is executed. Accordingly, the wearablesystem may not execute a command if the voice commands 2442 and thegesture 2426 indicate different user interactions (or virtual objects).By requiring both types of inputs, the wearable system can reduce thelikelihood that someone else hijacks the user's interaction.

As another example, one or more input modes may be disabled. Forexample, when a user is interacting with a document processingapplication, the head pose 2414 may be disabled as an input mode, asshown in FIG. 24 where the head pose slider 2424 is set to 0.

Each input may be associated with an authentication level. In FIG. 24,the voice 2412 is associated with the authentication level 2422; thehead pose 2414 is associated with the authentication level 2424; and thehand gesture 2416 is associated with the authentication level 2426. Theauthentication level may be used to determine whether an input isrequired for a command to be executed or whether an input is disabled orwhether the input is given a partial weight (between being fully enabledor fully disabled). As illustrated in FIG. 24, the authentication levelsof the voice 2412 and the hand gestures 2416 are set all the way to theright (which is associated with the maximum authentication level),suggesting that these two inputs are required for a command to issue. Asanother example, the authentication level of a head pose is set all theway to the left (which is associated with the minimum authenticationlevel). This suggests that head pose 2414 is not required for a commandto issue even though the head pose 2414 may still be used to determine atarget virtual object or a target user interface operation. In somesituations, by setting the authentication level to the minimum, thewearable system may disable head pose 2414 as an input mode.

In certain implementations, the authentication level may also be used tocalculate confidence levels associated with a virtual object. Forexample, the wearable system may assign a higher value to an input modewhich has a higher authentication level, while assigning a lower valueto an input mode which has a lower authentication level. As a result,when aggregating confidence scores from multiple input modes forcalculating an aggregated confidence score for a virtual object, theinput mode with a higher authentication level may have more weight inthe aggregated confidence score than the input mode with a lowerauthentication level.

The authentication levels can be set by a user (through inputs or via asetup panel) or can be set automatically by the wearable system, e.g.,based on indirect inputs. The wearable system may require more inputmodes when a user is in a public place while requiring fewer input modeswhen a user is in a private place. For example, the wearable system mayrequire both voice 2412 and hand gestures 2416 when the user is on asubway. However, when the user is at home, the wearable system mayrequire only the voice 2412 for issuing a command. As another example,the wearable system may disable the voice command when the user is in apublic park, thereby providing privacy to the user's interaction. Butthe voice command may still be available when the user is at home.

Although these examples are described with reference to setting directinput modes, similar techniques can also be applied to setting indirectinput modes as part of the multimodal input. For example, when a user isusing public transportation (such as, e.g., a bus), the wearable systemmay be configured to disable geolocation as an input mode because thewearable system may not know accurately where the user specifically sitsor stands on the public transportation.

Additional Example User Experiences

In addition to the examples described herein, this section describesadditional user experiences with multimodal inputs. As a first example,the multimodal inputs can include a voice input. For example, the usercan say a voice command such as “Hey Magic Leap, call her”, which isreceived by an audio sensor 232 on the HMD and parsed by the HMD system.In this command, the user can initiate the task (or provide aninitiation condition) by saying “Hey Magic Leap”. “Call” can be apreprogrammed word so the wearable system knows it should make atelephone call (rather than initiating a video call). In certainimplementations, these pre-programmed words can also be referred to as“hotwords” or “carrier phrases,” which the system recognizes asindicating the user wants to take a particular action (e.g., “Call”) andwhich may alert the system to accept further input to complete thedesired action (e.g., identify a person (“her”) or a telephone numberafter the word “Call”). The wearable system can use the additionalinputs to identify who “her” is. For example, the wearable system canuse eye tracking to see which contact on the virtual contact list or theuser's phone that the user is looking at. The wearable system can alsouse head pose or eye tracking to determine if the user is lookingdirectly at a person the user wants to call. In certain embodiments, thewearable system can utilize facial recognition techniques (e.g., usingthe object recognizers 708) to determine the identity of the person thatthe user is looking at.

As a second example, the user can have a virtual browser placed directlyon a wall (e.g., the display 220 of the wearable system can project thevirtual browser as if it is overlaid on the wall). The user can reachhis or her hand out and provide a tap gesture on a link in the browser.Since the browser appears to be on the wall, the user may tap the wallor tap in space such that the projection of the user's finger appears totap the wall to provide the indication. The wearable system can usemultimodal inputs to identify the link that the user intends to click.For example, the wearable system can use gesture detection (e.g., viadata acquired by the outward-facing imaging system 464), a head posebased cone-cast, and an eye gaze. In this example, the gesture detectionmay be less than 100% accurate. The wearable system can improve thegesture detection with data acquired from the head pose and eye gaze toincrease the gesture tracking's accuracy. For example, the wearablesystem can identify a radius where the eyes are most likely focusingbased on data acquired by the inward-facing imaging system 462. Incertain embodiments, the wearable system can identify the user's fieldof fixation based on the eye gaze. The wearable system can also useindirect input such as environment features (e.g., the location of thewall, the characteristics of the browser or the webpage, etc.) toimprove gesture tracking. In this example, the wall may be representedby a planar mesh (which may be previously stored in the map 920 of theenvironment), the wearable system can determine the user's hand positionin view of the planar mesh to determine the link that the user istargeting and selecting. Advantageously, in various embodiments, bycombining multiple modes of inputs, the accuracy required for one modeof input for a user interaction may be reduced as compared to a singlemode of input. For example, the FOV camera may not need to have veryhigh resolution for hand gesture recognition because the wearable systemcan supplement hand gestures with head pose or eye gaze to determine theintended user interaction.

Although the multimodal inputs in the examples above include an audioinput, the audio input is not required for the multimodal inputinteractions described above. For example, a user can use a 2D-touchswipe gesture (on a totem, for example) to move a browser window fromone wall to a different wall. The browser may initially be on the leftwall. The user can select the browser by actuating the totem. The usercan then look at the right wall and make a right-swipe gesture on thetouchpad of the totem. The swipe on the touchpad is loose and inaccuratebecause a 2D swipe by itself doesn't translate easily/well to a 3Dmovement. However, the wearable system can detect a wall (e.g., based onenvironmental data acquired by the outward-facing imaging system) anddetect the point where the user is specifically looking on the wall(e.g., based on eye gaze). With these three inputs (touch-swipe, gaze,environment features), the wearable system can gracefully place thebrowser at a location with high confidence that it is where the userwanted browser window to go.

Additional Examples of Head Pose as a Multimodal Input

In various embodiments, the multimodal inputs can support a totem freeexperience (or an experience where a totem is used infrequently). Forexample, multimodal inputs can include a combination of head pose andvoice control which can be used to share or search for a virtual object.The multimodal inputs can also use a combination of head pose andgestures to navigate various user interface planes and virtual objectswithin a user interface plane. A combination of head pose, voice, andgesture, can be used to move objects, conduct social networkingactivities (e.g., initiate and conduct a telepresence session, sharingposts), browse information on a webpage, or control a media player.

FIG. 25 illustrates an example of user experience with multimodal input.In the example scene 2500 a, the user 2510 can target and select theapplications 2512 and 2514 with a head pose. The wearable system candisplay a focus indicator 2524 a indicating that the user is currentlyinteracting with the virtual object with head pose. Once the userselects the application 2514, the wearable system may show a focusindicator 2524 a for the application 2514 (such as, e.g., a targetgraphic as shown in FIG. 25, a halo around the application 2514 orbringing the virtual object 2514 to appear closer to the user). Thewearable system can also change the focus indicator's appearance fromthe focus indicator 2524 a to the focus indicator 2524 b (e.g., thearrow graphic shown in the scene 2500 b) indicating that theinteractions by user input device 466 also become available after theuser selects with virtual object 2514. Voice and gesture interactionsextend this interaction pattern of head pose plus hand gestures. Forexample, when a user issues a voice command, the application targetedwith head pose may respond to or be manipulated by the voice command.Additional examples of interacting with virtual objects with acombination of, for example, head pose, hand gestures, and voicerecognition are described in U.S. application Ser. No. 15/296,869, filedOct. 18, 2016, titled “SELECTING VIRTUAL OBJECTS IN A THREE-DIMENSIONALSPACE”, published as U.S. Pat. Pub. No. 2017/0109936, the disclosure ofwhich is hereby incorporated by reference herein in its entirety.

The head pose may be integrated with voice control, gesture recognition,and environmental information (e.g., mesh information) to providehands-free browsing. For example, a voice command of “Search for FortLauderdale” will be handled by a browser if the user is using head poseto target the browser. If the user is not targeting a particularbrowser, the wearable system can also handle this voice command withoutgoing through a browser. As another example, when the user says “Sharethis with Karen”, the wearable system will execute the share action onan application that the user is targeting (e.g., using head pose, eyegaze, or gestures). As another example, the voice control can executebrowser window functions, such as, e.g., “Go to Bookmarks”, while thegestures may be used to perform basic navigation of a webpage such as,e.g., clicks and scrolls.

Multimodal inputs can also be used to launch and move a virtual objectwithout needing a user input device. The wearable system can usemultimodal inputs, such as, e.g., gesture, voice, and gaze, to naturallyplace content near a user and the environment. For example, the user canuse voice to open an unlaunched application when a user is interactingwith the HMD. The user can issue a voice command by saying “Hey MagicLeap, launch the Browser.” In this command, the initiation conditionincludes the presence of the invocation phrase “Hey Magic Leap”. Thecommand can be interpreted to include “launch” or “open” (which may beinterchangeable commands). The subject of this command is theapplication name e.g., “browser”. This command, however, does notrequire a parameter. In some embodiments, the wearable system canautomatically apply a default parameter, such as e.g., placing thebrowser in the user's environment (or the user's FOV).

The multimodal inputs can also be used to perform basic browsercontrols, such as, e.g., opening bookmarks, opening a new tab,navigating to history, etc. The ability to reference web content inhands-free or hands-full multi-tasking scenarios can empower users to bemore informed and productive. For example, a user, Ada, is a radiologistreading films in her office. Ada can navigate the web with voice andgesture to bring up reference material while reading the films, whichreduces her need to move a mouse back and forth to switch between thefilms and the reference materials on the screen. As another example, auser, Chris, is cooking a new recipe from a virtual browser window. Thevirtual browser window can be placed on his cabinet. Chris can use avoice command to pull up a bookmarked recipe while he starts choppingfood.

FIG. 26 illustrates an example user interface with a variety ofbookmarked applications. A user can select an application on the userinterface 2600 by saying the name of the application. For example, theuser can say “open food” to launch the food application. As anotherexample, the user can say “open this”. The wearable system can determinethe user's direction of gaze and identify an application on the userinterface 2600 that intersects with the user's direction of gaze. Thewearable system can accordingly open the identified application.

A user can also use a voice to issue a search command. The searchcommand can be performed by an application that the user is currentlytargeting. If the object does not currently support a search command,the wearable system may perform a search within a data store of thewearable system or search for the information via a default application(such as, e.g., via a browser). FIG. 27 illustrates an example userinterface 2700 when a search command is issued. The user interface 2700shows both an email application and a media watching application. Thewearable system may determine (based on the user's head pose) that theuser is currently interacting with the email application. As a result,the wearable system may automatically translate the user's voice commandinto a search command in the email application.

Multimodal inputs can also be used for media controls. For example, thewearable system can use voice and gesture controls to issue commandssuch as, e.g., play, pause, mute, fast forward, and rewind, forcontrolling a media player in an application (such as screens). Theusers can use the voice and gesture controls with a media applicationand set the totem aside.

Multimodal inputs can further be used in a social networking context.For example, a user can start conversations and share experiences (e.g.,virtual images, documents, etc.) without a user input device. As anotherexample, users can participate in a telepresence session and set aprivate context such that the users can feel comfortable for usingvoices to navigate the user interface.

Accordingly, in various implementations, the system may utilizemultimodal inputs such as: head pose plus voice (e.g., for informationsharing and general application searching), head pose plus gesture(e.g., for navigation in applications), or head pose plus voice plusgesture (e.g., for “put that there” functionality, media playercontrols, social interactions, or browser applications).

Additional Examples of Gesture Control as Part of Multimodal Inputs

There may be two, non-limiting and non-exclusive, classes of gestureinteractions: event gestures and dynamic hand tracking. Event gesturescan be in response to an event while a user is interacting with an HMD,such as, e.g., a catcher throwing a sign to a pitcher at a baseball gameor a thumbs-up sign at a browser window to cause the wearable system toopen a share dialogue. The wearable system can follow one or moregesture patterns that the user performs and respond to the eventaccordingly. Dynamic hand tracking can involve tracking the user's handwith low latency. For example, the user can move a hand over the user'sFOV and a virtual character may follow the movement of the user'sfinger.

The quality of gesture tracking may depend on the type of userinteraction. The quality may involve multiple factors, e.g., robustness,responsiveness, and ergonomics. In some embodiments, the event gesturesmay be near-perfect robustness. The threshold for minimum acceptablegesture performance may be a bit lower in social experiences,bleeding-edge interactions, and third party applications, since theaesthetics of these experiences can tolerate faults, interruptions, lowlatency, etc., but gesture recognition can still be highly performant inthese experiences to maintain the responsiveness.

To increase the likelihood that the wearable system is responsive to auser's gesture, the system can reduce or minimize latency for gesturedetection (for both event gestures and dynamic hand tracking). Forexample, the wearable system can reduce or minimize latency by detectingwhen the user's hand is within view of the depth sensor, automaticallyswitching the depth sensor to the appropriate gesture mode, and thengiving feedback to the user when he or she can perform the gesture.

As described herein, gestures can be used in combination with otherinput modes to launch, select, and move an application. Gesture can alsobe used to interact with virtual objects within an application, such asby tapping, scrolling in the air or on a surface (e.g., on a table or awall).

In certain embodiments, the wearable system can implement a socialnetworking tool which can support gesture interactions. A user canperform semantic event gestures to enrich communication. For example,the user can wave a hand in front of the FOV camera and a wave animationcan accordingly be sent to the person the user is chatting with. Thewearable system can also provide virtualization of a user's hands withdynamic hand tracking. For example, a user can hold up his or her handsin front of his or her FOV and get visual feedback that his or her handsare being tracked to animate his or her avatar's hands.

The hand gestures can also be used as part of the multimodal inputs formedia player controls. For example, the user can use a hand gesture toplay or to pause a video stream. The user can perform the gesturemanipulation away from the device (e.g., a television) playing thevideo. Upon detecting the user's gesture, the wearable system canremotely control the device based on the user's gesture. The user canalso look at the media panel and the wearable system can use the user'shand gesture in combination with the user's direction of gaze to updatethe parameters of the medial panel. For example, a pinch (ok) gesturemay suggest a “play” command a first gesture may suggest a “pause”command. The user can also close up the menu by waving one of the armsin front of the FOV camera. Examples of hand gestures 2080 are shown inFIG. 20.

Additional Examples of Interacting with Virtual Objects

As described herein, the wearable system can support various multimodalinteractions with objects (physical or virtual) in the user'senvironment. For example, the wearable system can support direct inputsfor interactions with found objects, such as targeting, selecting,controlling (e.g., the movement or properties) the found objects. Theinteractions with the found objects can also include interactions withfound object geometries or interactions with found object connectedsurfaces.

Direct inputs are also supported for interactions with flat surfaces,such as targeting and selecting wall or table top. The user can alsoinitiate various user interface events, such as, e.g., touch events, tapevents, swipe events, or scroll events. The user can manipulate 2D userinterface elements (e.g., panels) using direct interactions, such as,e.g., panel scrolling, swiping, and selecting elements (e.g., virtualobjects or user interface elements such as buttons) within a panel. Theuser can also move or resize the panel using one or more direct inputs.

Direct inputs can further be used to manipulate objects that are atdifferent depths. The wearable system can set various thresholddistances (from the user) to determine the region of the virtualobjects. With reference to FIG. 21, the objects that are within thedashed circle 2122 may be considered as objects in the near-field, theobjects that are within the dashed circle 2124 (but are outside of thedashed circle 2122) may be considered as objects in the mid field, andthe objects that are outside of the dashed circle 2124 may be consideredas objects in the far field. The threshold distance between the nearfield and the far field may be, e.g., 1 m, 2 m, 3 m, 4 m, 5 m, or more,and may depend on environment (e.g., larger in an outdoor park than anindoor office cubicle).

The wearable system can support various 2D or 3D manipulations ofvirtual objects in the near field. Example 2D manipulations may includemoving or resizing. Example 3D manipulations may include placing thevirtual objects in the 3D space such as by pinching, drawing, moving, orrotating the virtual objects. The wearable system can also supportinteractions with virtual objects in the mid field such as, e.g.,panning and repositioning the object in the user's environment,performing a radial motion of the object, or moving the object into thenear field or the far field.

The wearable system can also support continuous fingertip interactions.For example, the wearable system can allow the user's finger to pointlike an attractor, or pinpoint an object and perform a push interactionon the object. The wearable system can further support fast poseinteractions, such as, e.g., hand surface interactions or hand contourinteractions.

Additional Examples of Voice Command in the Context of Social Networkand Sharing

The wearable system can support voice commands as an input for a socialnetworking (or messaging) application. For example, the wearable systemcan support voice commands for sharing information with contacts ormaking calls with contacts.

As an example of starting a call with a contact, the user can use avoice command such as “Hey Magic Leap, call Karen.” In this command,“Hey Magic Leap” is the invocation phrase, the command is “call”, andthe parameter of the command is the name of the contact. The wearablesystem can automatically use a messenger application (as the subject) toinitiate the call. The command “call” may be associated with tasks, suchas, e.g., “start a call with”, start a chat with”, etc.

If the user says “Start a call” and then says a name, the wearablesystem can attempt to recognize the name. If the wearable system doesnot recognize the name, the wearable system can communicate a message tothe user for the user to confirm the name or contact information. If thewearable system recognizes the name, the wearable system may present adialog prompt which the user can confirm/deny (or cancel) the call, orprovide an alternative contact.

The user can also start a call with several contacts with a list offriends. For example, the user can say “Hey Magic Leap, start a groupchat with Karen, Cole, and Kojo.” The group chat command may beextracted from the phrase “start a group chat” or may be from a list offriends provided by the user. While a user is in a call, the user canadd another user to the conversation. For example, the user can say “HeyMagic Leap, invite Karen” where the phrase “invite” can be associatedwith an invite command.

The wearable system can share virtual objects with a contact using voicecommands. For example, the user can say “Hey Magic Leap, share Screenswith Karen” or “Hey Magic Leap, share that with David and Tony.” Inthese examples, the word “share” is a share command. The word “screens”or “that” may be a reference to a subject which the wearable system candetermine based on multimodal inputs. The names such as “Karen”, “Davidand Tony” are the parameters of the command. In some embodiments, whenthe voice command provided by the user includes the word “share” with anapplication reference and a contact, the wearable system may provide aconfirmation dialog to ask the user to confirm whether the user wants toshare the application itself or share a subject via the referencedapplication. When the user issues the voice command including the word“share”, an application reference, and a contact, the wearable systemcan determine whether the application name is recognized by the wearablesystem or whether the application exists on the user's system. If thesystem does not recognize the name or the application does not exist inthe user's system, the wearable system may provide a message to theuser. The message may suggest the user to try the voice command again.

If the user provides deictic or anaphoric references (e.g., “this” or“that”) in the voice command, the wearable system can use multimodalinputs (e.g., the user's head pose) to determine whether the user isinteracting with an object that can be shared. If the object cannot beshared, the wearable system may prompt an error message to the user ormove to a second mode of input, such as gestures, to determine whichobject should be shared.

The wearable system can also determine whether the contact with whom theobject is shared can be recognized (e.g., as part of the user's contactlist). If the wearable system recognizes the name of the contact, thewearable system can provide a confirmation dialogue to confirm that theuser wants to proceed with sharing. If the user confirms, the virtualobject can be shared. In some embodiments, the wearable system can sharemultiple virtual objects associated with an application. For example,the wearable system can share a whole album of pictures or share themost recently viewed picture in response to the user's voice command. Ifthe user denies sharing, the share command is canceled. If the userindicates that the contact is wrong, the wearable system may prompt theuser to speak the contact's name again or select a contact from a listof available contacts.

In certain implementations, if the user says “Share” and says anapplication reference but doesn't specify a contact, the wearable systemmay share the application locally with people in the user's environmentwho have access to the user's file. The wearable system may also replyand request the user to input a name using one or more of the inputmodes described herein. Similar to the social networking example, theuser can issue a voice command to share a virtual object with onecontact or a group of contacts.

A challenge in making calls via voice is when the Voice user interfaceincorrectly recognizes or fails to recognize a contact's name. This canbe especially problematic with less common or non-English names, e.g.,like lsi, Ileana, etc. For example, when a user says a voice commandincludes the name of a contact (such as “Share Screens with lly”), thewearable system may not be able to identify the name “lly” or itspronunciation. The wearable system can open a contacts dialogue with aprompt such as, e.g., “Who?” The user can try again with voice tospecify “Ily”, spell the name out “I-L-Y” using voice or a user inputdevice, or use a user input device to quickly select names from a panelof available names. The name “Ily” may be a nickname for Ileana, who hasan entry in the user's contacts. Once the user instructs the system that“Ily” is the nickname, the system may be configured to “remember” thenickname by automatically associating the nickname (or the pronunciationor audio pattern associated with the nickname) with the friend's name.

Additional Examples of Selecting and Moving a Virtual Object Using aVoice Command

A user can naturally and quickly manage the placement of a virtualobject in the user's environment using multimodal inputs, such as, e.g.,a combination of eye gaze, gestures, and voice. For example, a usernamed Lindsay sits down at the table and gets ready to do some work. Sheopens her laptop and starts up the desktop-Monitors app on her computer.As the computer is loading, she reaches her hand out above the laptopscreen and says “Hey Magic Leap, put Monitors here.” In response to thisvoice command, the wearable system can automatically launch the monitorscreens and place them above her laptop. However, when Lindsay says “Putscreens there” while looking over at the wall on the other side of theroom, the wearable system can automatically place the screens on thewall across from her. Lindsay could also say “Put halcyon here,” whilelooking at her desk. The halcyon was initially on her kitchen table, butin response to the voice command, the wearable system can automaticallymove it to her table surface. As she works, she can use a totem tointeract with these objects and adjust their scales to her preference.

The user can use voice to open an unlaunched application at any point inthe user's environment. For example, the user can say “Hey Magic Leap,launch the Browser.” In this command “Hey Magic Leap” is the invocationword, the word “launch” is a launch command, and the word “Browser” isan application of the subject. The “launch” commands may be associatedwith the words “launch”, “open”, “play”. For example, the wearablesystem can still identify the launch command when the user says “openthe browser”. In certain embodiments, an application may be an immersiveapplication which can provide a 3D virtual environment to a user as ifthe user is part of the 3D virtual environment. As a result, when theimmersive application is launched, the user may be positioned as if heis in the 3D virtual environment. In certain implementations, animmersive application also includes a store application. When the storeapplication is launched, the wearable system can provide a 3D shoppingexperience for the user so that the user can feel as if he is shoppingin a real store. In contrast to the immersive application, anapplication may be a landscape application. When the landscapeapplication is launched, it may be placed to where it would be placed iflaunched via totem in a launcher. As a result, the user can interactwith the landscape application, but the user may not feel that he ispart of the landscape application.

The user can also use a voice command to launch a virtual application ina specified location in the user's FOV or the user can move analready-placed virtual application (e.g., a landscape application) to aspecific location in the user's FOV. For example, the user can say “HeyMagic Leap, Put the browser here,” “Hey Magic Leap, Put the browserthere,” “Hey Magic Leap, Put this here,” or “Hey Magic Leap, Put thatthere.” These voice commands include the invocation word, the putcommand, the application name (which is a subject), and a location cue(which is a parameter). The subject may be referenced based on the audiodata, for example, based on the name of application spoken by the user.The subject may also be identified based on head pose or eye gaze whenthe user says the word “this” or “that” instead. To facilitate thisvoice interaction, the wearable system can make, for example, twoinferences: (1) which application to launch and (2) where to place theapplication.

The wearable system can use the put command and the application name toinfer which application to launch. For example, if the user says anapplication name that the wearable system doesn't recognize, thewearable system may provide an error message. If the user says anapplication name that the wearable system recognizes, the wearablesystem can determine whether the application has already been placedinto the user's environment. If the application is already shown in theuser's environment (such as, e.g., in the user's FOV), the wearablesystem can determine how many instances of the applications there are inthe user's environment (e.g., how many browser windows are open). Ifthere is just one instance of the target application, the wearablesystem can move the application to the location specified by the user.If there is more than one instance of the spoken application in theenvironment, the wearable system can move all instances of theapplication to the specified location or the most recently used instanceto the specified location. If the virtual application has not alreadybeen placed in the user's environment, the system can determine whetherthe application is a landscape application, an immersive application, ora store application (in which the user can download or purchase otherapplications). If the application is a landscape application, thewearable system can launch the virtual application at a specifiedlocation. If the application is an immersive application, the wearablesystem can place a shortcut of the application at the specified positionbecause the immersive application does not support the functions oflaunching at a specified location in the user's FOV. If the applicationis the store application, the system may place a mini store at thespecified position since the store application may require full 3Dimmersion of the user into the virtual world and therefore do notsupport launching at a specific location in the user's environment. Themini store may include brief summaries or icons of virtual objects inthe store.

The wearable system can use a variety of inputs to determine where toplace the application. The wearable system can parse the syntax in theuser's command (e.g., “here” or “there”), determine intersections ofvirtual objects in the user's environment with a head pose based raycast(or cone cast), determine the user's hand position, determine planarsurface mesh or environment planar mesh (e.g., a mesh associated with awall or a table), etc. As an example, if the user says “here”, thewearable system can determine the user's hand gesture, such as whetherthere is a flat open hand in the user's FOV. The wearable system canplace the object at the position of the user's flat hand and at arendering plane that is near the user's hand reach. If there are no flatopen hands in the FOV, the wearable system can determine whether a headpose (e.g., the direction of a head pose based cone cast) isintersecting with surface-planar mesh that is within the user'sarms-reach. If the surface-planar mesh exists, the wearable system canplace the virtual object at the intersection of the direction of thehead pose and the surface-planar mesh at a rendering plane that iswithin the user's arms-reach. The user can place the object flat on thesurface. If there is no surface planar mesh, the wearable system mayplace the virtual object at a rendering plane having distance somewherebetween within-arms-reach and optimal reading distance. If the user says“there”, the wearable system can perform similar operations as when theuser says “here”, except that if there is no surface-planar mesh that iswithin the user's arms-reach, the wearable system may place a virtualobject at a rendering plane in the mid field.

Once the user says “Put the Application . . . ”, the wearable system canimmediately provide predictive feedback to a user to show where thevirtual object would be placed based on available inputs if the usersays either “here” or “there”. This feedback could be in the form of afocus indicator. For example, the feedback may include a small floatingtext bubble saying “here” at the hand, mesh, or a planar surface whichintersects with the user's head pose direction at a rendering plane within the user's arms reach. The planar surface may be located in the nearfield if the user's command is “here” while in the mid or far field ifthe user's command is “there”. This feedback could be visualized like ashadow or the outline of the visual object.

The user can also cancel the interaction. An interaction may be canceledin two ways in various cases: (1) a command failed to be completed by ann second timeout or (2) input a canceling command, such as, e.g., saying“no”, “never mind’, or “cancel”.

Examples of Interacting with Text Using a Combination of User Inputs

Free form text input in a mixed reality environment, particularly inputof long string sequences, using traditional interaction modalities canbe problematic. As an example, systems that rely entirely upon automatedspeech recognition (ASR), especially in a “hands-free” environmentlacking input or interface devices such as keyboard, handheld controller(e.g., totem) or mouse, can be difficult to use for text editing (e.g.,to correct ASR errors endemic to speech recognition technology itselfsuch as an incorrect transcription of the user's speech). As anotherexample, a virtual keyboard in a “hands-free” environment may requirerefined user control and can cause fatigue if used as the primary formof user input.

The wearable system 200 described herein can be programmed to allow auser to naturally and quickly interact with virtual text usingmultimodal inputs, such as, e.g., a combination of two or more of:voice, eye gaze, gestures, head poses, totem inputs, etc. The phrase“text” as used herein can include a letter, a character, a word, aphrase, a sentence, a paragraph, or other types of free-form text. Textcan also include graphics or animations, e.g., emoji, ideograms,emoticons, smileys, symbols, etc. Interactions with the virtual text caninclude composing, selecting (e.g., selecting a portion of or all text),or editing text (e.g., change, copy, cut, paste, delete, clear, undo,redo, insert, replace, etc.), alone or in combination. By utilizing acombination of user inputs, the systems described herein providesignificant improvements in speed and convenience over single-inputsystems.

The multimodal text interaction techniques described herein can beapplied in any dictation scenario or application (e.g., in which thesystem simply transcribes user speech rather than applying any semanticevaluation, even if that transcription is part of another task that doesrely on semantic evaluation), Some example applications can include amessaging application, a word processing application, a gamingapplication, a system configuration application, etc. Examples of usecases can include a user writing a text message to be sent to a contactthat may or may not be in the user's contact list; a user writing aletter, an article, or other textual content; a user posting and sharingcontent on a social media platform; and a user completing or otherwisefilling out a form using the wearable system 200.

A system utilizing a combination of user inputs need not be a wearablesystem. If desired, such a system may be any suitable computing systemsuch as a desktop computer, a laptop, a tablet, a smart phone, oranother computing device having multiple user input channels such askeyboards, trackpads, microphones, eye or gaze tracking systems, gesturerecognition systems, etc.

Examples of Composing a Text with Multimodal User Inputs

FIGS. 28A-28F illustrate an example user experience of composing andediting a text based on a combination of inputs such as, e.g. voicecommands or eye gaze. As described herein, the wearable system candetermine the user's gaze direction based on images acquired by theinward-facing imaging system 462 shown in FIG. 4. The inward-facingimaging system 462 may determine the orientation of one or both of theuser's pupils and may extrapolate the line or lines of sight of theuser's eye or eyes. By determining the lines of sight of both eyes ofthe user, the wearable system 200 can determine the three-dimensionalposition in space in which the user is looking.

The wearable system can also determine a voice command based on dataacquired from the audio sensor 232 (e.g., a microphone) shown in FIG. 2.The system may have an automated speech recognition (ASR) engine thatconverts the spoken input 2800 into text. The speech recognition enginemay use natural language understanding in converting the spoken input2800 into text, including isolating and extracting message text from alonger utterance.

As shown in FIG. 28A, the audio sensor 232 can receive a phrase 2800spoken by a user. As illustrated in FIG. 28A, the phrase 2800 mayinclude a command, such as “Send a message to John Smith saying that,”as well as the parameters of the command such as, e.g., composing andsending a message, and the destination of the message as John Smith. Thephrase 2800 can also include the content of the message that is to becomposed. In this example, the content of the message can include “I'mflying in from Boston and will be there around seven o'clock; Period;Let's meet at the corner near the office.” Such content can be obtainedby parsing the audio data using an ASR engine (which can implementnatural language understanding to isolate and extract message contentand punctuation (e.g., “Period”) from the user's utterance). In someexamples, punctuation may be processed for presentation within thecontext of a transcribed string (e.g., “two o'clock” may be presented as“2:00” or “question mark” may be presented as “?”) The wearable systemcan also tokenize the text string, such as by isolating discrete wordsin the text string, and display the result, such as by displaying thediscrete words, in the mixed reality environment.

However, automatic speech recognition may be susceptible to errors insome situations. As illustrated in FIG. 28B, a system using an ASRengine may produce results that do not precisely match the user's spokeninput, for various reasons including poor or idiosyncraticpronunciation, environmental noise, homonyms and other similar soundingwords, hesitations or disfluency, and vocabulary that is not in theASR's dictionary (e.g., foreign phrases, technical terms, jargon, slang,etc.). In the example of FIG. 28B, the system properly interpreted thecommand aspect of the phrase 2800 and generated a message with a header2802 and a body 2804. However, in the body 2804 of the message, thesystem incorrectly interpreted the user's utterance of “corner” as“quarter,” which are somewhat similar sounding. In systems that relyentirely upon voice inputs, it would be difficult for a user to quicklyreplace the misrecognized word (or phrase) with the intended word (orphrase). However, the wearable system 200 described herein canadvantageously allow the user quickly correct the error as illustratedin FIGS. 28C-28F.

The ASR engine in the wearable system may produce text results,including at least one word, associated with a user's utterance and mayalso produce an ASR score associated with each word (or phrase) in thetext results. A high ASR score may indicate a high confidence or highlikelihood that the ASR engine correctly transcribed the user'sutterance into text, whereas a low ASR score may indicate a lowconfidence or low likelihood that the ASR engine correctly transcribedthe user's utterance into text. In some embodiments, the system maydisplay words with low ASR scores (e.g., ASR scores below an ASRthreshold) in an emphasized manner (e.g., with background highlighting,italics or bold font, different color font, etc.), which may make iteasier for the user to identify or select incorrectly recognized words.A low ASR score for a word can indicate that the user is more likely toselect that word for editing or replacement, because there is areasonable likelihood that the ASR engine mis-recognized the word.

As shown in FIGS. 28C and 28D, the wearable system may enable the userto select the misrecognized word (or phrase) using an eye trackingsystem, such as inward-facing imaging system 462 of FIG. 4. In thisexample, the selected word may be an example of the target virtualobject described above with earlier figures.

The wearable system 200 can determine the gaze direction based on theinward-facing imaging system 462 and can cast a cone 2806 or ray in thegaze direction. The wearable system can select one or more words thatintercept with the user's direction of gaze. In certain implementations,a word may be selected when the user's gaze lingers on the erroneousword for at least a threshold time. As described above, the erroneousword may by determined at least in part by being associated with a lowASR score. The threshold time may be any amount of time sufficient toindicate that the user wants to select a particular word, but not solong as to unnecessarily delay selection. The threshold time may also beused to determine a confidence score indicating that the user desires toselect a particular virtual word. For example, the wearable system cancalculate the confidence score based on how long a user has stared at adirection/object, where the confidence score may increase as the timeduration for looking at a certain direction/object increases. Theconfidence score may also be calculated based on multimodal inputs asdescribed herein. For example, the wearable system may determine, with ahigher confidence score (than the confidence score derived from eye gazealone), if both the user's hand gesture and the eye gaze indicate a wordshould be selected.

As another example, the wearable system may calculate the confidencescore based in part on the ASR score, which may be indicative of therelative confidence of the ASR engine of a translation of a particularword, as discussed in more detail herein. For example, a low ASR enginescore may be indicative that the ASR engine has relatively lowconfidence that it correctly transcribed a spoken word. Therefore, thereis a higher probability that the user will be likely to select that wordfor editing or replacement. If the user's gaze lingers longer than athreshold time on a word that has a low ASR score, the system can assigna higher confidence score to reflect that the user has selected thatword for at least two reasons: first, the length of the eye gaze on theword and second, the fact that the word was likely mis-transcribed bythe ASR engine, both of which tend to indicate that the user is going towant to edit or replace that word.

A word may be selected if the confidence score passes a thresholdcriterion. As examples, the threshold time may be one-half a second, onesecond, one and a half seconds, two seconds, two and a half seconds,between one and two seconds, between one and three seconds, etc. Thus,the user can easily and quickly select the erroneous word, “quarter,”merely by looking at it for a sufficient time. The word may be selectedbased on a combination of eye gaze (or gesture) time together with anASR score above an ASR threshold, both of which criteria provideindications that the user is going to select that particular word.

As an example, if the results of the ASR engine include a first wordhaving a high ASR score (e.g., a word the ASR engine is relativelyconfident was correctly recognized) and a second word having a low ASRscore (e.g., a word the ASR engine is relatively confident was notcorrectly recognized) and these two words are displayed adjacent to eachother by the wearable system, the wearable system may assume that auser's gaze input that encompasses both the first and second words isactually an attempt by the user to select the second word, based on itsrelatively low ASR score, because the user is more likely to want toedit the incorrectly recognized second word than the correctlyrecognized first word. In this manner, words produced by an ASR enginewith a low ASR score, which are more likely to be inaccurate and requireediting, may be significantly easier for a user to select for editing,thus facilitating editing by the user.

Although this example describes selecting the misrecognized word usingeye gaze, another multimodal input can also be used to select a word.For example, cone casting can identify multiple words, such as “around”,“7:00”, “the”, and “quarter”, since they also intersect with a portionof the virtual cone 2806. As will further be described with reference toFIGS. 29-31, the wearable system can combine the eye gaze input withanother input (such as e.g., a gesture, a voice command, or an inputfrom a user input device 466) to select the word “quarter” as the wordfor further editing.

Upon selecting the word 2808, the system can enable editing of theselected word. The wearable system can allow a user to edit the wordusing a variety of techniques, such as, e.g., change, cut, copy, paste,delete, clear, undo, redo, insert, replace, etc. As shown in FIG. 28D,the wearable system can allow a user to change the word 2808 to anotherword. The wearable system can support a variety of user inputs forediting the word 2808, such as, e.g., by receiving additional spokeninput through a microphone to replace or delete the selected word,displaying a virtual keyboard to enable the user to type out areplacement, or receiving user input via a user input device, etc. Incertain implementations, an input may be associated with a specific typeof text editing. For example, a waving gesture may be associated withdeleting the selected text while a gesture with a finger pointing at aposition in the text may cause the wearable system to insert additionaltext at the position. The wearable system can also support a combinationof user inputs to edit the words. As will further be described withreference to FIGS. 32-35, the system can support eye gaze in combinationwith another input mode to edit the word.

In the examples of FIGS. 28D and 28E, the system may automaticallypresent the user with an array of suggested alternatives such asalternatives 2810 a and 2810 b upon a selection of the word 2808. Thesuggested alternatives may be generated by the ASR engine or otherlanguage processing engines in the system and may be based on theoriginal speech input (which may also be referred to as voice input insome embodiments), natural language understandings, context, learnedfrom user behavior, or other suitable sources. In at least someembodiments, suggested alternatives may be alternate hypothesesgenerated by the ASR engine, may be hypotheses generated by a predictivetext engine (which may try to “fill in the blanks” using the context ofadjacent words and a user's historical patterns of text), may behomophones of the original translation, may be generated using athesaurus, or may be generated using other suitable techniques. In theillustrated examples, the suggested alternatives to “quarter” include“corner” and “courter”, which may be provided by a language engine asbeing words that sound similar to “quarter.”

FIG. 28E illustrates how the system may enable the user to select adesired alternative word, such as “corner,” with eye gaze. The wearablesystem may use similar techniques as those described with reference toFIG. 28C to select the alternative word. For example, the system maytrack the user's eyes using inward-facing imaging system 462 todetermine that the user's gaze 2812 has been focused upon a particularalternative, such as alternative 2810A or “corner”, for at least athreshold time. After determining that the user's gaze 2812 was focusedon an alternative for the threshold time, the system may revise the text(the message) by replacing the originally selected word with theselected alternative word 2814, as shown in FIG. 28F. In certainimplementations, where the wearable system uses cone casting to select aword, the wearable system can dynamically adjust the size of the conebased on the density of the text. For example, the wearable system maypresent a cone with a bigger aperture (and thus with a bigger surfacearea at the away from the user) to select an alternative word forediting as shown in FIG. 28E because there are few available options.But the wearable system may present the cone with a smaller aperture toselect the word 2808 in FIG. 28C because the word 2808 is surroundedwith other words and a smaller cone can reduce the error rate ofaccidentally selecting another word.

The wearable system can provide feedback (e.g., visual, audio, haptic,etc.) to the user throughout the course of operation. For example, thewearable system can present a focus indicator to facilitate the user'srecognition of the target virtual object. For example, as shown in FIG.28E, the wearable system can provide a contrasting background 2830around the word “quarter” to show that the word “quarter” is selectedand the user is currently editing the word “quarter”. As anotherexample, as shown in FIG. 28F, the wearable system can change the fontof the word “corner” 2814 (e.g., to a bold font) to show that thewearable system has confirmed the replacement of the word “quarter” withthis alternative word “corner”. In other implementations, the focusindicator can include a cross-hair, a circle or oval surrounding theselected text, or other graphical techniques to highlight or emphasizethe selected text.

Examples of Selecting a Word with Multimodal User Inputs

The wearable system can be configured to support and utilize multiplemodes of user inputs to select a word. FIGS. 29-31 illustrate examplesof selecting a word based on a combination of eye gaze and another inputmode. Although in other examples, inputs other than eye gaze can also beused in combination with another mode of inputs for interactions withtexts.

FIG. 29 illustrates an example of selecting a word based on an inputfrom a user input device and gaze. As shown in FIG. 29, the system maycombine a user's gaze 2900 (which may be determined based on data fromthe inward-facing imaging system 462) together with a user inputreceived via a user input device 466. In this example, the wearablesystem can perform a cone cast based on the user's direction of gaze.The wearable system can confirm the selection of the word “quarter”based on the input from the user input device. For example, the wearablesystem can identify that the word “quarter” is the word that is closestto the user's gaze direction and the wearable system can confirm thatthe word quarter is selected based on the user's actuation of the userinput device 466. As another example, the cone cast can capture aplurality of words, such as, e.g., “around”, “7:00”, “the”, and“quarter”. The user can select the word, via the user input device 466,among the plurality of words for further editing. By receiving inputindependent of the user's gaze, the system may not need to wait as longbefore confidently identifying a particular word as one the user wantsto edit. After selecting a word to edit in this manner, the system maypresent alternatives (as discussed in connection with FIG. 28E) orotherwise allow the user to edit the selected word. The same process ofcombining the user's gaze with a user input received via a totem may beapplied to selecting a desired replacement word (e.g., selecting theword “corner” among the alternatives to replace the word “quarter”).Some implementations may utilize a confidence score to determine whichtext is being selected by the user. The confidence score may aggregatemultiple input modalities to provide a better determination of theselected text. For example, the confidence score may be based on thetime that the user gazes at the text, whether the user actuates the userinput device 466 when gazing at the text, whether the user points towardthe selected text, and so forth. If the confidence score passes athreshold, the wearable system can determine, with increased confidence,that the system has correctly selected the text the user wants. Forexample, to select text just with eye gaze, the system may be configuredto select the text if the gaze time exceeds 1.5 seconds. However, if theuser gazes at the text for only 0.5 seconds but simultaneously actuatesthe user input device, the system can more quickly and confidentlydetermine the selected text, which may improve the user experience.

FIG. 30 illustrates an example of selecting a word for editing based ona combination of voice and gaze inputs. The wearable system candetermine a target virtual object based on the user's gaze. As shown inFIG. 30, the system may determine that a user's gaze 3000 is directed toa particular word (in this case “quarter”). The wearable system can alsodetermine the operation to be performed on the target virtual objectbased on the user's voice command. For example, the wearable system mayreceive a user's spoken input 3010 via the audio sensor 232, mayrecognize the spoken input 3010 as a command, and may combine the twouser inputs into a command to apply the command operation (“edit”) tothe target virtual object (e.g., the word the user is focusing theirgaze upon (“quarter”)). As discussed previously, the system may presentalternative words after a user selects a word for editing. The sameprocess of combining the user's gaze with a spoken input may be appliedto selecting a desired replacement word among the alternative words toreplace the word “quarter”. As described herein, a term like “edit”represents a context-specific wakeup word that serves to invoke aconstrained system command library associated with editing for each ofone or more different user input modalities. That is, such a term, whenreceived by the system as spoken input may cause the system to evaluatesubsequently-received user input against a limited set of criteria so asto recognize editing-related commands provided by the user with enhancedaccuracy. For example, within the context of speech input, the systemmight consult a limited command-specific vocabulary of terms to performspeech recognition on subsequently-received speech input. In anotherexample, within the context of gaze or gesture input, the system mightconsult a limited command-specific library of template images to performimage recognition on subsequently-received gaze or gesture input. A termlike “edit” is sometimes referred to as a “hotword” or “carrier phrase,”and the system may include a number of pre-programmed (and optionally,user-settable) hotwords such as (in the editing context): edit, cut,copy, paste, bold, italic, delete, move, etc.

FIG. 31 illustrates an example of selecting a word for editing based ona combination of gaze and gesture inputs. As illustrated in the exampleof FIG. 31, the system may use eye gaze input 3100 together with gestureinput 3110 to select a word for editing. In particular, the system maydetermine an eye gaze input 3100 (e.g., based on data acquired by theinward-facing imaging system 462) and may identify a gesture input 3110(e.g., based on images acquired by the outward-facing imaging system464). Object recognizers such as the recognizers 708 may be used indetecting part of a user's body, such as their hand, making a gestureassociated with identification of a word for editing.

The gesture may be used alone or in combination with the eye gaze toselect a word. For example, although the cone cast can capture multiplewords, the wearable system may nevertheless identify the word “quarter”as the target virtual object because it is identified both from conecast and the user's hand gesture (e.g., a confidence score based on theeye gaze cone cast in addition to the hand gesture passes a confidencethreshold indicating the user selected the word “quarter”). As anotherexample, although the cone cast can capture multiple words, the wearablesystem may nevertheless identify the word “quarter” as the targetvirtual object because it is identified both from cone cast and is theword with the lowest ASR score from the ASR engine that lies within (ornear) the cone cast. In certain implementations, a gesture may beassociated with a command operation, as it can be associated with acommand such as “edit” or the other hotwords described herein. As anexample, the system may recognize when a user points to the same wordthey are gazing at, and interpret these user inputs as a request to editthe same word. If desired, the system may also utilize additional userinput, such as a voice command to “edit” at the same time, indetermining that the user wants to edit a particular word.

Examples of Editing a Word with Multimodal User Inputs

Once the user has selected a word for editing, the system can utilizeany desirable mode of user input to edit the selected word. The wearablesystem can allow a user to change or replace the selected word bydisplaying a list of potential alternatives and receiving user gazeinput 2812 to select an alternative word to replace the original word(see example illustrated in FIG. 28E). FIGS. 32-34 illustrate additionalexamples of editing a selected word where the selected word can beedited using multimodal inputs.

FIG. 32 illustrates an example of replacing a word based on acombination of eye gaze and speech inputs. In FIG. 32, the systemreceives a speech input 3210 from the user (through audio sensor 232 orother suitable sensor). The speech input 3210 can contain the desiredreplacement word (which may or may not be a replacement word from thelist of suggested alternatives 3200). Upon receiving the speech input3210, the wearable system can parse the input (e.g. to strip out carrierphrases like “change this to . . . ”) to identify the word spoken by theuser and replace the selected word “quarter” with the word “corner” asuttered by the user. Although in this example, the replacement is aword, in certain implementations, the wearable system can be configuredto replace the word “quarter” with a phrase or a sentence or some otherelement (e.g., an emoji). In examples where multiple words are containedwithin the eye gaze cone cast, the wearable system may automaticallyselect the word within the eye gaze cone that is closest to thereplacement word (e.g. “quarter” is closer to “corner” than “the” or“7:00”).

FIG. 33 illustrates an example of changing a word based on a combinationof voice and gaze inputs. In this example, the wearable system canreceive a speech input 3310 and determine the user's gaze direction3300. As shown in FIG. 33, the speech input 3310 includes the phrase“change it to ‘corner’”. The wearable system can parse the speech input3310 and determine that the speech input 3310 includes a commandoperation “change” (which is an example of a carrier phrase), a subject“it”, and a parameter of the command (e.g., a resulting word “corner”).This speech input 3310 can be combined with the eye gaze 3300 todetermine the subject of the operation. As described with reference toFIGS. 28A and 28B, the wearable system can identify the word “quarter”as the subject of the operation. Thus, the wearable system can changethe subject (“quarter”) to the resulting word “corner”.

FIG. 34 illustrates an example of editing a selected word 3400 using avirtual keyboard 3410. The virtual keyboard 3410 can be controlled byuser gaze inputs, gesture inputs, inputs received from a user inputdevice, etc. For example, a user may type out a replacement word bymoving the eye gaze direction 3420 over the virtual keyboard 3410displayed to the user by the display of the wearable system 200. Theuser may type each letter in the replacement word by pausing their gazeover a respective key for a threshold period of time, or the wearablesystem may recognize changes in direction of the user's gaze 3420 over aparticular key as an indication the user wants to select that key(thereby eliminating the need for the user to hold their focus steady oneach individual key when typing out a word). As described with referenceto FIG. 28D, in certain implementations, the wearable system may varythe size of the cone based on the size of the keys. For example, in avirtual keyboard 3410 where the size of each key is relatively small,the wearable system may reduce the size of the cone to allow a user toidentify the letters in the replacement word more accurately (such thata cone cast will not accidentally capture a large number of possiblekeys). If the size is relatively big, the wearable system canaccordingly increase the size of the keys to so that the user does nothave to pinpoint the gaze direction (which can reduce fatigue).

In certain implementations, after a word has been selected, the wearablesystem can present a set of possible actions in addition to or inalternative to displaying a list of suggested alternative words forreplacing the selected word. The user 210 can select an action and editthe selected word using the techniques described herein. FIG. 35illustrates an example user interface that displays possible actions toapply to a selected word. In FIG. 35, upon selection of a word 3500 forediting, the wearable system may present a list 3510 of options forediting, including (in this example) an option to (1) change the word(using any of the techniques described herein for editing), (2) cut theword out and optionally store it in a clipboard or copy the word andstore it in a clipboard, or (3) paste in a word or phrase from theclipboard. Additional or alternative options that may be presentedinclude a delete selection option, an undo option, a redo option, aselect all option, an insert here option, and a replace option. Thevarious options may be selected using gaze input, totem input, gestureinput, etc. as described herein.

Examples of Interacting with a Phrase with Multimodal User Inputs

While the preceding examples have described using multimodal inputs toselect and edit a word, this is intended for illustration, and the sameor similar processes and inputs may generally be used in selecting andediting a phrase or a sentence or a paragraph including multiple wordsor characters.

FIGS. 36(i)-36(iii) illustrates an example of interacting with a phraseusing multimodal inputs. At FIG. 36(i), the wearable system candetermine the user's gaze 3600 direction, and perform and cone castbased on the user's gaze direction. At FIG. 36(ii), the system mayrecognize that the gaze 3600 of the user 210 is focused on a first word3610 (e.g., “I'm”). The system may make such determinations of the firstword 3610 using any of the techniques discussed herein, including butnot limited to recognizing that the user's gaze 3600 has dwelled (e.g.,lingered) on a particular word for a threshold period of time, that theuser's gaze 3600 is on a particular word at the same time the userprovides voice, gesture, or totem input, etc. The wearable system canalso display a focus indicator (e.g., a contrasting background as shown)on the selected word “I'm” 3610 to indicate that the word has beendetermined from the eye gaze cone cast. The user can actuate a totem3620 (which is an example of the user input device 466) while looking atthe first word 3610. This actuation may indicate that the user intendsto select a phrase or a sentence beginning with the first word 3610.

At FIG. 36(iii), after the actuation of the user input device 466, theuser can look at the last intended word (e.g., the word “there”) toindicate that the user desires to select the phrase starting from theword “I'm” and ending at the word “there”. The wearable system can alsodetect that the user has stopped actuating the totem 3620 (e.g.,releasing the button that the user previously pressed) and canaccordingly select the entire range 3630 of the phrase “I'm flying infrom Boston and will be there”. The system can display the selectedphrase using a focus indicator (e.g., by extending the contrastingbackground to all the words in the phrase).

The system may determine that the user desires to select a phrase ratherthan another word for editing using a variety of techniques. As anexample, the system may determine that the user desires to select aphrase rather than undo their selection of the first word when the userselects a second word shortly after the user selects a first word. Asanother example, the system may determine that the user wants to selecta phrase when the user selects a second word that appears after thefirst and the user has not yet edited the first selected word. As yetanother example, the user may press a button on totem 3620 when they arefocused on first word 3610 and then hold the button until their gaze hassettled on the last word. When the system recognizes the button waspressed while the gaze 3610 was focus on a first word, but only releasedafter the user's gaze 3610 shifted to a second word, the system mayrecognize the multimodal user input as a selection of a phrase. Thesystem may then identify all of the words in the phrase, including thefirst word, the last word, and all words in between and may enableediting of the phrase as a whole. The system may use a focus indicatorto highlight the selected phrase (e.g., highlighting, emphasized text(e.g., bold or italic or a different color), etc.) so that it stands outfrom unselected text. The system may then display contextuallyappropriate options for editing the selected phrase, such as options3510, a virtual keyboard such as keyboard 3410, alternative phrases,etc. The system may receive additional user inputs such as spoken input,totem input, gesture input, etc. to determine how to edit the selectedphrase 3630.

While FIG. 36 illustrates the user selecting a first word 3610 that isat the start of a phrase, the system may also allow a user to selectbackwards from the first word 3610. In other words, the user may selecta phrase by selecting the last word of a phrase (e.g., “there”), andthen by selecting the first word of the desired phrase (e.g., “I'm”).

FIGS. 37A-37B illustrate another example of interacting with a textusing multimodal inputs. In FIG. 37A, a user 210 utters a sentence (“Iwant to sleep”). The wearable system can capture the user's utterance asa speech input 3700. For this speech input, the wearable system candisplay both primary and secondary results from the automated speechrecognition (ASR) engine for each word, as shown in FIG. 37B. Theprimary result for each word may represent the ASR engine's best guess(e.g., the word having the highest ASR score for indicating what wordthe user actually spoke) for the word spoken by the user in speech input3700, whereas the secondary results may represent similarly soundingalternatives or words having lower ASR scores than the ASR engine's bestguess. In this figure FIG. 37B, the primary results are displayed as thesequence 3752. In some embodiments, the wearable system may presentalternative results or hypotheses as alternative phrases and/or entiresentences as opposed to alternative words. As an example, the wearablesystem may provide a primary result of “four score and seven years ago”along with a secondary result of “force caring seven years to go” wherethere is no one-to-one correspondence between discrete words in theprimary and secondary results. In such embodiments, the wearable systemcan support inputs from the user (in any of the manners describedherein) selecting the alternative or secondary phase(s) and/orsentence(s).

As shown in FIG. 37B, each word from the user's speech input 3700 may bedisplayed as a collection 3710, 3720, 3730, 3740 of primary andsecondary results. Arrangements of this type may enable a user toquickly swap out incorrect primary results and correct any errorsintroduced by the ASR engine. The primary results 3752 may be emphasizedwith a focus indicator (e.g., each word is in bold text surrounded by abounding box in the example in FIG. 37B) to distinguish them from thesecondary results.

The user 210 can dwell on secondary results, e.g., secondary words,phrases, or sentences etc., if the primary words are not the onesintended by the user. As an example, the ASR engine's primary result incollection 3740 is “slip,” whereas the correct transcription is actuallythe first secondary result “sleep.” To correct this error, the user canfocus their gaze upon the correct secondary result “sleep” and thesystem may recognize that the user's gaze lingering upon a secondaryresult for a threshold period of time. The system may translate the usergaze input as a request to replace the primary result “slip” with theselected secondary result “sleep.” Additional user inputs may bereceived in conjunction with selecting a desired secondary result, suchas user speech input (e.g., the user may ask the system to “edit”, “usethis”, or “replace” while looking at the desired secondary result).

Once the user finishes editing the phrase “I want to sleep” or confirmsthat the transcription is correct, the phrase can be added to a body oftext using any modes of user input described herein. For example, theuser can say a hotword, such as “finish” to cause the edited phrase tobe added back to a body of text.

Example Processes of Interacting with Text Using a Combination of UserInputs

FIG. 38 is a process flow diagram of an example method 3800 of usingmultiple modes of user input to interact with a text. The process 3800can be performed by the wearable system 200 described herein.

At block 3810, the wearable system may receive spoken input from a user.The speech input may include the user's speech containing one or morewords. In one example, the user may dictate a message and the wearablesystem may receive this dictated message. This may be achieved throughany suitable input device, such as the audio sensor 232.

At block 3820, the wearable system may transform the speech input intotext. The wearable system may utilize an automatic speech recognition(ASR) engine to transform the user's spoken input into text (e.g., aliteral transcription), and may further leverage natural languageprocessing techniques to transform such text into a semanticrepresentation indicative of intents and concepts. The ASR engine may beoptimized for free-form text input.

At block 3830, the wearable system may tokenize the text into discreteactionable elements such as words, phrases, or sentences. The wearablesystem may also display the text for the user, using a display systemsuch as the display 220. In some embodiments, the wearable system doesnot need to understand the meaning of the text during the tokenizationsystem. In other embodiments, the wearable system is equipped with thecapacities to understand the meaning of the text (e.g., one or morenatural language processing models or other probabilistic statisticalmodels), or simply the capacities to distinguish between (i) words,phrases, and sentences that represent a user-composed message or portionthereof, and (ii) words, phrases, and sentences that do not represent auser-composed message or portion thereof, but instead correspond tocommands to be executed by the wearable system. For example, thewearable system may need to know the meaning of the text for recognizinga command operation or a parameter of the command spoken by the user.Examples of such text may include context-specific wakeup words thatserve to invoke one or more constrained system command librariesassociated with editing for each of one or more different user inputmodalities, which are also referred to herein as hotwords.

A user can interact with one or more of the actionable elements usingmultimodal user inputs. At block 3840, the wearable system can selectone or more elements in response to a first indication. The firstindication can be one user input or a combination of user inputs asdescribed herein. The wearable system may receive input from the userselecting one or more of the elements of the text string for editing.The user may select a single word or multiple words (e.g., a phrase or asentence). The wearable system may receive a user input selectingelement(s) for editing in any desired form including, but not limitedto, a speech input, a gaze input (e.g., via the inward-facing imagingsystem 462), a gesture input (e.g., as captured by the outward-facingimaging system 464), a totem input (e.g., via actuation of a user inputdevice 466), or any combinations thereof. As examples, the wearablesystem may receive a user input in the form of a user's gaze lingeringon a particular word for a threshold period of time or may receive auser's gaze on a particular word at the same time as a user input via amicrophone or totem indicating a selection of that particular word forediting.

At block 3850, the wearable system can edit the selected element(s) inresponse to a second indication. The second indication can be receivedvia a single mode of input or a combination of input modes as describedwith preceding figures including, but not limited to, user gaze input,spoken input, gesture input, and totem input. The wearable system mayreceive user input indicating how the selected element(s) should beedited. The wearable system may edit the selected element(s) accordingto the user input received in block 3850. For example, the wearablesystem can replace the selected element based on a speech input. Thewearable system can also present a list of suggested alternatives andchoose among the selected alternatives based on the user's eye gaze. Thewearable system can also receive input via user interactions with avirtual keyboard or via a user input device 466 (such as, e.g., aphysical keyboard or a handheld device).

At block 3860, the wearable system can display a result of editing theselected element(s). In certain implementations, the wearable system canprovide a focus indicator on the element(s) that is edited.

As indicated by the arrow 3870, the wearable system may repeat blocks3840, 3850, and 3860 if the user provides additional user input to editadditional element(s) of the text.

ADDITIONAL ASPECTS

In a 1st aspect, a method for interacting with virtual content,comprising: receiving a first direct user input, determining a firstconfidence score correlated to the first direct user input, receiving asecond direct user input, determining a second confidence scorecorrelated to the second direct user input, calculating an aggregateconfidence score from at least the first confidence score and secondconfidence score, manipulating a subject virtual object to meet aparameter condition.

In a 2nd aspect, the method of aspect 1, wherein the first direct userinput is selected from the group consisting of speech input, handgesture, head pose, and eye gaze.

In a 3rd aspect, the method of any one of aspects 1-2, wherein thesecond direct user input is selected from the group consisting of speechinput, hand gesture, head pose, and eye gaze.

In a 4th aspect, the method of any one of aspects 1-3, wherein aparameter is a position of the subject virtual object.

In a 5th aspect, the method of any one of aspects 1-4, wherein aparameter is a size of the subject virtual object.

In a 6th aspect, the method of any one of aspects 1-5, wherein aparameter is a functionality of the subject virtual object.

In a 7th aspect, a method for interacting with virtual content,comprising: receiving a direct user input, determining a firstconfidence score correlated to the direct user input, receiving anindirect user input, determining a second confidence score correlated tothe indirect user input, calculating an aggregate confidence score fromat least the first confidence score and second confidence score,manipulating a subject virtual object to meet a parameter condition.

In a 8th aspect, the method of aspect 7, wherein the direct user inputis selected from the group consisting of speech input, hand gesture,head pose, and eye gaze.

In a 9th aspect, the method of aspect 8, wherein the indirect user inputis geolocation.

In a 10th aspect, the method of any one of aspects 7-8, wherein aparameter is a position of the subject virtual object.

In an 11th aspect, the method of any one of aspects 7-10, wherein aparameter is a size of the subject virtual object.

In a 12th aspect, the method of any one of aspects 7-11, wherein aparameter is a functionality of the subject virtual object.

The method of any one of aspects 1-12 above can be performed undercontrol of the wearable system 200 described herein.

In a 13th aspect, a system for interacting with objects for a wearabledevice, the system comprising: a display system of a wearable deviceconfigured to present a three-dimensional (3D) view to a user and permita user interaction with objects in a field of regard (FOR) of a user,the FOR comprising a portion of the environment around the user that iscapable of being perceived by the user via the display system; ahardware processor in communication with the sensor and the displaysystem, the hardware processor programmed to: receive multimodal inputsfor a user interaction; parse the multimodal inputs to identify asubject, a command, and a parameter of the user interaction; and executethe user interaction based on the subject, the command, and theparameter.

In a 14th aspect, the system of aspect 13, wherein the system comprisesat least one of: a microphone, an inertial measurement unit, anoutward-facing imaging system, or an inward-facing imaging system.

In a 15th aspect, the system of aspect 14, wherein the multimodal inputscomprise direct inputs comprising at least one of: a head pose, an eyegaze, a hand gesture, or a speech input.

In a 16th aspect, the system of any one of aspects 13-14, wherein themultimodal inputs comprises at least one of: an input from a user inputdevice or an indirect input, where the indirect input comprises alocation of the user or a location of an object in an environment of theuser.

In a 17th aspect, the system of any one of aspects 13-16, wherein thesubject comprises a target virtual object that a user intends tointeract, wherein the command comprises an action that the wearablesystem performs on the target virtual object, and wherein the parametercomprises an characteristics of the action.

In an 18th aspect, the system of aspect 17, wherein the parametercomprises a placement, an orientation, a destination position of thetarget virtual object.

In a 19th aspect, the system of any one of aspects 13-18, wherein toidentify the subject of the user interaction, the wearable device isprogrammed to: access a first value to a first input of the multimodalinputs; access a second value to a second input of the multimodalinputs; calculate a first confidence score based for a first candidatevirtual object based on the first or the second value; calculate asecond confidence score for a second candidate virtual object based onthe first or the second value; and set the subject to be either thefirst candidate virtual object or the second candidate virtual objectbased on a comparison of the first confidence score.

In a 20th aspect, the system of aspect 19, wherein the first input isassociated with a first weight and the second input is associated with asecond weight, and wherein the first value and the second value areassigned based on the first weight and the second weight respectively.

In a 21st aspect, the system of any one of aspects 13-20, wherein thecomputer processor is further configured to: detect an initiationcondition associated with the user interaction, wherein the initiationcondition comprises an invocation phrase or a hand gesture.

In a 22nd aspect, the system of aspect 21, wherein the initiationcondition comprises a combination of two input modes, wherein the twoinput modes consistently indicate the user interaction.

In a 23rd aspect, the system of any one of aspects 13-22, wherein theprocessor is further programmed to: receive environment data from anenvironmental sensor of the wearable device; and automatically settingan authentication level associated with an input mode based on theenvironment data.

In a 24th aspect, the system of any one of aspects 13-23, wherein theuser interaction comprises at least one of: selecting or moving avirtual object, conducting a telepresence session, modifying the virtualobject, or sharing the virtual object with another wearable device.

In a 25th aspect, the system of any one of aspects 13-24, wherein themultimodal inputs comprise head pose and speech input.

In a 26th aspect, the system of aspect 25, wherein the multimodal inputsfurther comprise a gesture or eye gaze.

In a 27th aspect, a system comprising: a first sensor configured toacquire first user input data in a first mode of input; a second sensorconfigured to acquire second user input data in a second mode of input,the second mode of input different from the first mode of input; and ahardware processor in communication with the first and second sensors.The system may be a wearable system for interacting with objects and thefirst sensor and the second sensor may be part of the wearable system.The hardware processor of the system can be programmed to: receivemultimodal inputs comprising the first user input data in the first modeof input and the second user input data in the second mode of input;identify a first set of candidate objects for interactions based on thefirst user input data; identify a second set of candidate objects forinteractions based on the second user input data; determine a targetvirtual object from the first set of candidate objects and the secondset of candidate objects based on a combination of the first user inputdata and the second user input data; determine a user interfaceoperation on the target virtual object based on at least one of thefirst user input data or the second user input data; and generate amultimodal input command which causes the user interface operation to beperformed on the target virtual object.

In a 28th aspect, the system of aspect 27, wherein the multimodal inputscomprise at least two of the following input modes: head pose, eye gaze,user input device, hand gesture, or voice.

In a 29th aspect, the system of aspect 27 or 28, wherein the userinterface operation comprises at least one of selecting, moving, orresizing the target virtual object.

In a 30th aspect, the system of any one of aspects 27-29, wherein thehardware processor is further configured to determine at least one of: atarget location, orientation, or movement for the target virtual objectin the user interface operation.

In a 31st aspect, the system of aspect 30, wherein to determine thetarget location for the target virtual object, the hardware processor isprogrammed to identify a workable surface in a physical environment forputting the target virtual object.

In a 32nd aspect, the system of aspect 31, wherein the workable surfaceis identified by: calculating a distance function for points of interest(POIs) on a physical object in the physical environment; eliminating oneor more of the POIs outside of a planar tolerance; and delineating theworkable surface based on remaining POIs.

In a 33rd aspect, the system of aspect 31 or 32, wherein the hardwareprocessor is programmed to automatically orient the target virtualobject to match an orientation of the target location.

In a 34th aspect, the system of any one of aspects 27-33, wherein theoperation is determined based on the first user input data in the firstinput mode, and at least one of the subject or the parameter isdetermined based on a combination of the first mode of input and thesecond mode of input.

In a 35th aspect, the system of any one of aspects 27-34, wherein thefirst input mode comprises an indirect input mode based on locationinformation of a user of the wearable system.

In a 36th aspect, the system of aspect 35, wherein the hardwareprocessor is programmed to identify a virtual object as the targetvirtual object from the first set of objects and the second set ofobjects in response to a determination that the object is within athreshold range of the user.

In a 37th aspect, the system of aspects 27-36, wherein the userinterface operation is associated with a virtual application and thevirtual application is programmed to be more responsive to one of thefirst sensor or the second sensor.

In a 38th aspect, the system of aspects 27-37, wherein to determine thetarget virtual object from the first set of candidate objects and thesecond set of candidate objects, the hardware processor is programmed toperform a tree-based analysis on the first set of candidate objects andthe second set of the candidate objects based on the first user inputdata and the second user input data.

In a 39th aspect, the system of aspect 38, wherein to determine thetarget virtual object from the first set of candidate objects and thesecond set of candidate objects, the hardware processor is programmedto: calculate a first confidence score for a candidate object in thefirst set of candidate objects based on the first user input data;calculate a second confidence score for the candidate object based onthe second user input data; calculate an aggregated score for thecandidate object from at least the first confidence score and the secondconfidence; and set the candidate object as the target virtual object inresponse to a determination that the aggregated score meets a thresholdcondition.

In a 40th aspect, the system of any one of aspects 27-39, wherein todetermine the target virtual object, the hardware processor isprogrammed to calculate a confidence score for a virtual object bycalculating at least one of: an evenness of space around the virtualobject in the field of view; a proportional area for a first portion thevirtual object that is in the user's field of view with respect to asecond portion of the virtual object that is outside of the user's fieldof view; or a historical analysis of user's interactions with thevirtual object.

In a 41st aspect, the system of any one of aspects 27-40, wherein thehardware processor is further programmed to: detect an initiationcondition for the interaction event which triggers the hardwareprocessor to determine the target virtual object and the user interfaceoperation based on the multimodal inputs.

In a 42nd aspect, the system of aspect 41, wherein the initiationcondition comprises a triggering phrase.

In a 43rd aspect, the system of any one of aspects 27-42, wherein thefirst mode of input is a primary input mode and the second mode of inputis a secondary input mode, and the hardware processor is programmed to:resolve ambiguities in at least one of the target virtual object and theuser interface operation based on the second user input data.

In a 44th aspect, the system of any one of aspects 27-43, wherein thefirst user input data comprises a deictic or anaphoric reference to avirtual object and hardware processor is programmed to identify thevirtual object as the target virtual object as the subject based on thesecond user input data.

In a 45th aspect, the system of aspects 27-44, wherein the hardwareprocessor is further programmed to automatically enable, disable, oradjust a sensitivity of the first mode of input, the second mode ofinput, or both based at least in part on a user setting or anenvironment of the user.

In a 46th aspect, the system of aspects 27-45, wherein the hardwareprocessor is programmed to identify that target virtual object outsideof a field of view of the user based at least in part on the multimodalinputs; and automatically move the virtual object inside the field ofview for user interaction.

In a 47th aspect, a method is described. The method can be forinteracting with objects and can performed under control of a hardwareprocessor of a wearable system in communication of a plurality ofsensors configured to acquire user input data. The method can comprise:receiving the user input data from the plurality of sensors for aninteraction event of a user with an environment; analyzing the userinput data to identify multimodal inputs for interacting with theenvironment wherein the multimodal inputs comprise a first input in afirst input channel and a second input in a second input channel;determining, based on the first input and the second input, a multimodalinput command which comprises one or more of a subject, a parameter, oran operation for describing the interaction event with the environment,wherein at least one of the subject, the parameter, or the operation isidentified based on a combination of the first input and the secondinput; and causing the wearable device to execute the multimodal inputcommand for the interaction event.

In a 48th aspect, the method of aspect 47, wherein the operationcomprises at least one of selecting, moving, or resizing the subject;wherein the subject comprises a target virtual object with which theuser is about to interact; or wherein the parameter comprises at least atarget location, orientation, or movement of the subject.

In a 49th aspect, the method of aspect 48, wherein the target locationis determined by: calculating a distance function for points of interest(POIs) on a physical object; eliminating one or more of the POIs outsideof a given planar tolerance; and delineating the workable surface on thephysical object based on remaining POIs.

In a 50th aspect, the method of aspect 48 or 49, wherein the methodcomprises automatically orienting the virtual object to match that ofthe target location.

In a 51st aspect, the method of any one of aspects 47-50, wherein themultimodal inputs comprise at least two of the following input modes:head pose, eye gaze, user input device, hand gesture, or voice.

In a 52nd aspect, the method of aspect 51, wherein the first inputchannel is voice and the second input channel is a head pose or handgesture.

In a 53rd aspect, the method of any one of aspects 47-52, wherein atleast one of the operation, subject, or parameter is further identifiedbased on environment or location information of the user.

In a 54th aspect, the method of aspect 53, wherein the subject isselected from a group of objects within a threshold range of the user.

In a 55th aspect, the method of any one of aspects 47-54, wherein theinteraction event is within a virtual application and the virtualapplication is programmed to be more responsive to one of the firstinput channel or the second input channel.

In a 56th aspect, the method of any one of aspects 47-55, wherein thesubject is identified by analyzing the first input and the second inputusing a lattice tree analysis to identified a virtual object for settingas the subject.

In a 57th aspect, the method of any one of aspects 47-56, wherein thesubject or the parameter in the multimodal input command is determinedby: calculating, for a candidate object or parameter, a first confidencescore correlating to the first input and a second confidence scorecorrelating to the second input; and calculating an aggregated score forthe candidate object or parameter from at least the first confidencescore and the second confidence; and setting the candidate object orparameter as the subject or the parameter respectively for theinteraction event based at least in part on the aggregated score.

In a 58th aspect, the method of any one of aspects 47-57, wherein acandidate virtual object is identified as the subject based onconfidence scores of virtual objects in a field of view of the user; andwherein the confidence code is calculated based on at least one of: anevenness of space around the candidate virtual object in the field ofview; a proportional area for a first portion the candidate virtualobject that is in the user's field of view with respect to a secondportion of the candidate virtual object that is outside of the user'sfield of view; or a historical analysis of user's interactions with thecandidate virtual object.

In a 59th aspect, the method of any one of aspects 47-58, furthercomprising: detecting an initiation condition for the interaction eventbased on data received from one or more sensors of the plurality ofsensors, wherein the initiation condition triggers the receiving,analyzing, determining and causing steps.

In a 60th aspect, the method of any one of aspects 47-59, wherein thefirst input from the first input channel is a primary input and thesecond input from the second input channel is a secondary input, and themethod comprises: parsing the first input to identify the subject, theparameter, and the operation, and resolving ambiguities in at least oneof the subject, the parameter, or the operation based on the secondinput to generate the multimodal input command.

In a 61st aspect, the method of any one of aspects 47-60, wherein themethod further comprises automatically enabling, disabling, or adjustinga sensitivity an input channel based at least in part on a user settingor the environment of the user.

In a 62nd aspect, the method of any one of aspects 47-61, wherein themethod further comprises identifying a virtual object that is outside ofa field of view of the user as the subject based at least in part on theuser interaction; and automatically move the virtual object inside thefield of view for user interaction.

In a 63rd aspect, the method of any one of aspects 47-62, wherein thefirst input comprises a deictic or anaphoric reference as the subjectand the method further comprising selecting a target object as thesubject based on the second input.

In a 64th aspect, a system comprising: a head-mounted display (HMD)configured to present three dimensional (3D) virtual content to a user;two or more user input components configured to receive user input of arespective modality, wherein one of the user input components comprisesan audio sensing device configured to capture sound; and a hardwareprocessor communicatively coupled to the display and the two or moreuser input components. The HMD may be part of a wearable system. Thehardware processor may be programmed to: receive, from the audio sensingdevice, speech data encoding an utterance of one or more words spoken bythe user; obtain a transcription for the one or more words spoken by theuser based at least on the received speech data; control the display topresent a string of textual characters representative of the obtainedtranscription to the user; receive, from another of the two or more userinput components, user input data indicating user input of another,different modality; determine that the user input data received from theother user input component represents a command to select a particularsubset of the textual characters for editing; and in response to thedetermination that the user input data received from the other userinput component represents the command to select the particular subsetof the textual characters for editing: determine whethersubsequently-received data from any of the two or more user inputcomponents represents a command to modify the particular subset of thetextual characters in a particular manner.

In a 65th aspect, the system of aspect 64, wherein the other user inputcomponent comprises an eye gaze tracking device configured to acquiredata indicating the user's eye gaze direction.

In a 66th aspect, the system of aspect 65, wherein the hardwareprocessor is further programmed to: determine, based at least on datareceived from the eye gaze tracking device, that the user has fixated onthe particular subset of the textual characters for longer than athreshold period of time; and determine that the user input datareceived from the other user input component represents the command toselect the particular subset of the textual characters for editing inresponse to a determination that the user has fixated on the particularsubset of the textual characters for longer than a threshold period oftime.

In a 67th aspect, the system of aspect 65 or 66, wherein the hardwareprocessor is further programmed to: receive, from the audio sensingdevice, additional speech data encoding an utterance of a phrase spokenby the user; and determine, based at least on data received from the eyegaze tracking device and the additional speech data received from theaudio sensing device, that the user has uttered one or morepredetermined hotwords while fixated on the particular subset of thetextual characters, in response to a determination that the user hasuttered one or more predetermined hotwords while fixated on theparticular subset of the textual characters, determine that the datareceived from eye gaze tracking device and the additional speech datareceived from the audio sensing device represent the command to selectthe particular subset of the textual characters for editing.

In a 68th aspect, the system of any one of aspects 65-67, wherein thetwo or more user input components further comprise a gesture trackingdevice configured to acquire data indicating the user's hand gestures,wherein the hardware processor is further programmed to: receive, fromthe eye gaze tracking device, data indicating the user's eye gazedirection; receive, from the gesture tracking device, data indicatingthe user's hand gestures; determine, based at least on the data receivedfrom the eye gaze tracking device and the data received from the gesturetracking device, that the user has made one or more predetermined handgestures while fixated on the particular subset of the textualcharacters, and in response to a determination that the user has madeone or more predetermined hand gestures while fixated on the particularsubset of the textual characters, determine that the data received fromthe eye gaze tracking device and the gesture tracking device representsthe command to select the particular subset of the textual charactersfor editing.

In a 69th aspect, the system of any one of aspects 65-68, wherein thetwo or more user input components further comprise a touch-sensitivedevice configured to acquire data indicating the user's physicalinteraction therewith, wherein the hardware processor is furtherprogrammed to: receive, from the eye gaze tracking device, dataindicating the user's the user's eye gaze direction; receive, from thetouch-sensitive device, data indicating the user's physical interactionthe touch-sensitive device; determine, based at least on the datareceived from the eye gaze tracking device and the data received fromthe touch-sensitive device, whether the user has provided one or morepredetermined touch inputs while fixated on the particular subset of thetextual characters; and in response to a determination that the user hasprovided one or more predetermined touch inputs while fixated on theparticular subset of the textual characters, determine that the datareceived from eye gaze tracking device and the touch-sensitive devicerepresents the command to select the particular subset of the textualcharacters for editing.

In a 70th aspect, the system of any one of aspects 64-69, wherein thehardware processor is programmed to implement an automated speechrecognition (ASR) engine to obtain the transcription.

In a 71st aspect, the system of aspect 70, wherein the ASR engine isconfigured to produce a score associated with one or more words in thestring of text, which indicates a likelihood that the ASR enginecorrectly transcribed such words.

In a 72nd aspect, the wearable system of aspect 71, wherein the hardwareprocessor is further programmed to cause the HMD to emphasize the one ormore words if the likelihood of correct transcription is below athreshold level.

In a 73rd aspect, a system comprising: a display configured to presentvirtual content to a user; an audio sensing device configured to capturewords spoken by the user and to generate speech data; an eye gazetracking device configured to track a gaze of the user; and a hardwareprocessor communicatively coupled to the display, the audio sensingdevice, and the eye gaze tracking device. The system may be a wearablesystem and the hardware processor may be programmed to: obtain atranscription of one of more words spoken by the user into text, basedat least in part on the speech data from the audio sensing device;control the display to present the text to the user; determine, based atleast on data received from the eye gaze tracking device, that the userhas given a command to select a portion of the presented text forediting; and perform an editing action on the portion of the presentedtext.

In a 74th aspect, the system of aspect 73, wherein the hardwareprocessor is further programmed to determine that the user has given thecommand to select the given word for editing based on data from the eyegaze tracking device indicating that the user's gaze has lingered on theportion of the presented text presented by the display for at least athreshold period of time.

In a 75th aspect, the system of aspect 73 or 74, further comprising auser input device, wherein the hardware processor is further programmedto determine that the user has given the command to select the portionof the presented text for editing based on data from the user inputdevice and data from the eye gaze tracking device indicating that theuser input device received user input while the user's gaze was focusedon the portion of the presented text presented by the display.

In a 76th aspect, the system of any one of aspects 73-75, wherein thehardware processor is programmed to determine that the user has giventhe command to select the portion of the presented text for editingbased on data from the audio sensing device and data from the eye gazetracking device indicating that the audio sensing device received avoice command while the user's gaze was focused on the portion of thepresented text presented by the display.

In a 77th aspect, the system of any one of aspects 73-76, furthercomprising an imaging system that images at least one hand of the user,wherein the processor is configured to determine that the user has giventhe command to select the portion of the presented text for editingbased on data from the imaging system and data from the eye gazetracking device indicating that the user made a command gesture withtheir hand while the user's gaze was focused on the portion of thepresented text presented by the display.

In a 78th aspect, the system of any one of aspects 73-77, wherein thehardware processor is further programmed to: control the display topresent alternative transcriptions of the portion of the presented textin response to the command to select the given word for editing.

In a 79th aspect, the system of any one of aspects 73-78, wherein thehardware processor is further programmed to: determine, based onadditional data received from the eye gaze tracking device, that theuser has given a command to replace the portion of the presented textwith a selected alternative transcription; revise the text to replacethe portion of the presented text with the selected alternativetranscription; and control the display to present the revised text tothe user.

In an 80th aspect, the system of any one of aspects 73-79, wherein thehardware processor is further programmed to produce a score associatedwith one or more words in the text, which indicates a likelihood thatsuch words are correctly transcribed.

In an 81st aspect, the wearable system of aspect 80, wherein thehardware processor is further programmed to cause the display toemphasize the one or more words if the likelihood of correcttranscription is below a threshold level.

In an 82nd aspect, a method comprising: receiving spoken input from auser from a microphone; translating the spoken input into text includinga plurality of words; causing a wearable display to present the text tothe user; based at least on data from a gaze tracking system, receivinga selection of a portion of the presented text in the displayed text;and providing the user with an opportunity to edit the portion of thepresented text. The method can be for interacting with virtual contentbased on multimodal inputs and the method may be performed under controlof a hardware processor.

In an 83rd aspect, the method of aspect 82, wherein receiving theselection of the portion of the presented text comprises one or more of:determining that the user's gaze was focused on the given word for atleast a predetermined threshold period of time; determining that theuser's gaze is focused on the portion of the presented text whilereceiving a spoken predetermined command from the user requesting anedit with the microphone; determining that the user's gaze is focused onthe portion of the presented text while receiving data for an actuationof a user input device; or determining that the user's gaze is focusedon the portion of the presented text and substantially while receivingdata from a gesture tracking system indicating that the user made apredetermined command gesture requesting an edit.

In an 84th aspect, the method of aspect 82 or 83, further comprising:based at least one data from the gaze tracking system, receiving aselection of an additional word in the displayed text; and providing theuser with an opportunity to edit a phrase formed from the portion of thepresented text or an additional portion of the text.

In an 85th aspect, the method of any one of aspects 82-84, wherein atleast a portion of the text is emphasized on the display where theportion is associated with a low confidence that a translation from thespoken input to the corresponding portion of the text is correct.

In an 86th aspect, a method comprising: receiving a multimodal inputcomprising: first user input from a hardware component of a wearabledevice, wherein the first user input is associated with a first mode ofuser input, and a second user input, wherein the second user input isassociated with a second mode of user input; identifying a multimodalinput command based on the first user input and the second user input,wherein the multimodal input command comprising at least: a subjectcomprising at least a portion of a text, and a command operationcomprising an interaction with the text, and executing the multimodalinput command and to cause a result of the user multimodal input to bedisplayed to a user. The method can be performed under control of ahardware processor and may be for interacting virtual content based onmultimodal inputs.

In an 87th aspect, the method of aspect 86, wherein the first mode ofuser input comprises a speech input received from an audio sensor of thewearable device, wherein the method further comprising transcribing thespeech input to identify at least one of the text, the subject, or thecommand operation.

In an 88th aspect, the method of aspect 86 or 87, wherein the secondmode of user input comprises an input from at least one of: a user inputdevice, a gesture, or an eye gaze.

In an 89th aspect, the method of any one of aspects 86-88, wherein theinteraction with the text comprises at least one of: selecting, editing,or composing the text.

In a 90th aspect, the method of any one of aspects 86-89, wherein thesubject comprises one or more of: a word, a phrase, or a sentence.

In a 91st aspect, the method of any one of aspects 86-90, wherein thesubject comprises a sentence and the command operation comprisesselecting the sentence for editing, and the method further comprises:performing a first user interface operation causing to bring thesentence out of a body of text; displaying the sentence as a sequence oftokens as primary results wherein the primary results comprise thesentence as transcribed from the user's speech; further displayingsecondary results, wherein the secondary results comprise alternativewords to tokens in the sequence; receiving another multimodal inputcomprising a third mode of input and a fourth mode of input for editingthe sequence on a word by word basis; and inserting the edited sequenceback to the body of text in response to an indication that the editingof the sequence has been completed.

Additional Considerations

Each of the processes, methods, and algorithms described herein and/ordepicted in the attached figures may be embodied in, and fully orpartially automated by, code modules executed by one or more physicalcomputing systems, hardware computer processors, application-specificcircuitry, and/or electronic hardware configured to execute specific andparticular computer instructions. For example, computing systems caninclude general purpose computers (e.g., servers) programmed withspecific computer instructions or special purpose computers, specialpurpose circuitry, and so forth. A code module may be compiled andlinked into an executable program, installed in a dynamic link library,or may be written in an interpreted programming language. In someimplementations, particular operations and methods may be performed bycircuitry that is specific to a given function.

Further, certain implementations of the functionality of the presentdisclosure are sufficiently mathematically, computationally, ortechnically complex that application-specific hardware or one or morephysical computing devices (utilizing appropriate specialized executableinstructions) may be necessary to perform the functionality, forexample, due to the volume or complexity of the calculations involved orto provide results substantially in real-time. For example, a video mayinclude many frames, with each frame having millions of pixels, andspecifically programmed computer hardware is necessary to process thevideo data to provide a desired image processing task or application ina commercially reasonable amount of time.

Code modules or any type of data may be stored on any type ofnon-transitory computer-readable medium, such as physical computerstorage including hard drives, solid state memory, random access memory(RAM), read only memory (ROM), optical disc, volatile or non-volatilestorage, combinations of the same and/or the like. The methods andmodules (or data) may also be transmitted as generated data signals(e.g., as part of a carrier wave or other analog or digital propagatedsignal) on a variety of computer-readable transmission mediums,including wireless-based and wired/cable-based mediums, and may take avariety of forms (e.g., as part of a single or multiplexed analogsignal, or as multiple discrete digital packets or frames). The resultsof the disclosed processes or process steps may be stored, persistentlyor otherwise, in any type of non-transitory, tangible computer storageor may be communicated via a computer-readable transmission medium.

Any processes, blocks, states, steps, or functionalities in flowdiagrams described herein and/or depicted in the attached figures shouldbe understood as potentially representing code modules, segments, orportions of code which include one or more executable instructions forimplementing specific functions (e.g., logical or arithmetical) or stepsin the process. The various processes, blocks, states, steps, orfunctionalities can be combined, rearranged, added to, deleted from,modified, or otherwise changed from the illustrative examples providedherein. In some embodiments, additional or different computing systemsor code modules may perform some or all of the functionalities describedherein. The methods and processes described herein are also not limitedto any particular sequence, and the blocks, steps, or states relatingthereto can be performed in other sequences that are appropriate, forexample, in serial, in parallel, or in some other manner. Tasks orevents may be added to or removed from the disclosed exampleembodiments. Moreover, the separation of various system components inthe implementations described herein is for illustrative purposes andshould not be understood as requiring such separation in allimplementations. It should be understood that the described programcomponents, methods, and systems can generally be integrated together ina single computer product or packaged into multiple computer products.Many implementation variations are possible.

The processes, methods, and systems may be implemented in a network (ordistributed) computing environment. Network environments includeenterprise-wide computer networks, intranets, local area networks (LAN),wide area networks (WAN), personal area networks (PAN), cloud computingnetworks, crowd-sourced computing networks, the Internet, and the WorldWide Web. The network may be a wired or a wireless network or any othertype of communication network.

The systems and methods of the disclosure each have several innovativeaspects, no single one of which is solely responsible or required forthe desirable attributes disclosed herein. The various features andprocesses described above may be used independently of one another, ormay be combined in various ways. All possible combinations andsubcombinations are intended to fall within the scope of thisdisclosure. Various modifications to the implementations described inthis disclosure may be readily apparent to those skilled in the art, andthe generic principles defined herein may be applied to otherimplementations without departing from the spirit or scope of thisdisclosure. Thus, the claims are not intended to be limited to theimplementations shown herein, but are to be accorded the widest scopeconsistent with this disclosure, the principles and the novel featuresdisclosed herein.

Certain features that are described in this specification in the contextof separate implementations also can be implemented in combination in asingle implementation. Conversely, various features that are describedin the context of a single implementation also can be implemented inmultiple implementations separately or in any suitable subcombination.Moreover, although features may be described above as acting in certaincombinations and even initially claimed as such, one or more featuresfrom a claimed combination can in some cases be excised from thecombination, and the claimed combination may be directed to asubcombination or variation of a subcombination. No single feature orgroup of features is necessary or indispensable to each and everyembodiment.

Conditional language used herein, such as, among others, “can,” “could,”“might,” “may,” “e.g.,” and the like, unless specifically statedotherwise, or otherwise understood within the context as used, isgenerally intended to convey that certain embodiments include, whileother embodiments do not include, certain features, elements and/orsteps. Thus, such conditional language is not generally intended toimply that features, elements and/or steps are in any way required forone or more embodiments or that one or more embodiments necessarilyinclude logic for deciding, with or without author input or prompting,whether these features, elements and/or steps are included or are to beperformed in any particular embodiment. The terms “comprising,”“including,” “having,” and the like are synonymous and are usedinclusively, in an open-ended fashion, and do not exclude additionalelements, features, acts, operations, and so forth. Also, the term “or”is used in its inclusive sense (and not in its exclusive sense) so thatwhen used, for example, to connect a list of elements, the term “or”means one, some, or all of the elements in the list. In addition, thearticles “a,” “an,” and “the” as used in this application and theappended claims are to be construed to mean “one or more” or “at leastone” unless specified otherwise.

As used herein, a phrase referring to “at least one of” a list of itemsrefers to any combination of those items, including single members. Asan example, “at least one of: A, B, or C” is intended to cover: A, B, C,A and B, A and C, B and C, and A, B, and C. Conjunctive language such asthe phrase “at least one of X, Y and Z,” unless specifically statedotherwise, is otherwise understood with the context as used in generalto convey that an item, term, etc. may be at least one of X, Y or Z.Thus, such conjunctive language is not generally intended to imply thatcertain embodiments require at least one of X, at least one of Y and atleast one of Z to each be present.

Similarly, while operations may be depicted in the drawings in aparticular order, it is to be recognized that such operations need notbe performed in the particular order shown or in sequential order, orthat all illustrated operations be performed, to achieve desirableresults. Further, the drawings may schematically depict one more exampleprocesses in the form of a flowchart. However, other operations that arenot depicted can be incorporated in the example methods and processesthat are schematically illustrated. For example, one or more additionaloperations can be performed before, after, simultaneously, or betweenany of the illustrated operations. Additionally, the operations may berearranged or reordered in other implementations. In certaincircumstances, multitasking and parallel processing may be advantageous.Moreover, the separation of various system components in theimplementations described above should not be understood as requiringsuch separation in all implementations, and it should be understood thatthe described program components and systems can generally be integratedtogether in a single software product or packaged into multiple softwareproducts. Additionally, other implementations are within the scope ofthe following claims. In some cases, the actions recited in the claimscan be performed in a different order and still achieve desirableresults.

1-37. (canceled)
 38. A system comprising: a head-mounted display (HMD)of a wearable system configured to present three dimensional (3D)virtual content to a user; two or more user input components configuredto receive user input of a respective modality, wherein one of the userinput components comprises an audio sensing device configured to capturesound; and a hardware processor communicatively coupled to the displayand the two or more user input components, the hardware processorprogrammed to: receive, from the audio sensing device, speech dataencoding an utterance of one or more words spoken by the user; obtain atranscription for the one or more words spoken by the user based atleast on the received speech data; control the display to present astring of textual characters representative of the obtainedtranscription to the user; receive, from another of the two or more userinput components, user input data indicating user input of another,different modality; determine that the user input data received from theother user input component represents a command to select a particularsubset of the textual characters for editing; and in response to thedetermination that the user input data received from the other userinput component represents the command to select the particular subsetof the textual characters for editing: determine whethersubsequently-received data from any of the two or more user inputcomponents represents a command to modify the particular subset of thetextual characters in a particular manner.
 39. The system of claim 38,wherein the other user input component comprises an eye gaze trackingdevice configured to acquire data indicating an eye gaze direction ofthe user.
 40. The system of claim 39, wherein the hardware processor isfurther programmed to: determine, based at least on data received fromthe eye gaze tracking device, that the user has fixated on theparticular subset of the textual characters for longer than a thresholdperiod of time; and determine that the user input data received from theother user input component represents the command to select theparticular subset of the textual characters for editing in response to adetermination that the user has fixated on the particular subset of thetextual characters for longer than a threshold period of time.
 41. Thesystem of claim 39, wherein the hardware processor is further programmedto: receive, from the audio sensing device, additional speech dataencoding an utterance of a phrase spoken by the user; determine, basedat least on data received from the eye gaze tracking device and theadditional speech data received from the audio sensing device, that theuser has uttered one or more predetermined hotwords while fixated on theparticular subset of the textual characters; and in response to adetermination that the user has uttered one or more predeterminedhotwords while fixated on the particular subset of the textualcharacters, determine that the data received from eye gaze trackingdevice and the additional speech data received from the audio sensingdevice represent the command to select the particular subset of thetextual characters for editing.
 42. The system of claim 39, wherein thetwo or more user input components further comprise a gesture trackingdevice configured to acquire data indicating hand gestures of the user,wherein the hardware processor is further programmed to: receive, fromthe eye gaze tracking device, data indicating the eye gaze direction;receive, from the gesture tracking device, data indicating the handgestures; determine, based at least on the data received from the eyegaze tracking device and the data received from the gesture trackingdevice, that the user has made one or more predetermined hand gestureswhile fixated on the particular subset of the textual characters, and inresponse to a determination that the user has made one or morepredetermined hand gestures while fixated on the particular subset ofthe textual characters, determine that the data received from the eyegaze tracking device and the gesture tracking device represents thecommand to select the particular subset of the textual characters forediting.
 43. The system of claim 39, wherein the two or more user inputcomponents further comprise a touch-sensitive device configured toacquire data indicating physical interactions therewith, wherein thehardware processor is further programmed to: receive, from the eye gazetracking device, data indicating the eye gaze direction; receive, fromthe touch-sensitive device, data indicating the physical interactionswith the touch-sensitive device; determine, based at least on the datareceived from the eye gaze tracking device and the data received fromthe touch-sensitive device, whether the user has provided one or morepredetermined touch inputs while fixated on the particular subset of thetextual characters; and in response to a determination that the user hasprovided one or more predetermined touch inputs while fixated on theparticular subset of the textual characters, determine that the datareceived from eye gaze tracking device and the touch-sensitive devicerepresents the command to select the particular subset of the textualcharacters for editing.
 44. The system of claim 38, wherein the hardwareprocessor is programmed to implement an automated speech recognition(ASR) engine to obtain the transcription.
 45. The system of claim 44,wherein the ASR engine is configured to produce a score associated withone or more words in the string of text, which indicates a likelihoodthat the ASR engine correctly transcribed such words.
 46. The system ofclaim 45, wherein the hardware processor is further programmed to causethe HMD to emphasize the one or more words if the likelihood of correcttranscription is below a threshold level.
 47. A system comprising: adisplay of a wearable system configured to present virtual content to auser; an audio sensing device configured to capture words spoken by theuser and to generate speech data; an eye gaze tracking device of thewearable system configured to track a gaze of the user; and a hardwareprocessor communicatively coupled to the display, the audio sensingdevice, and the eye gaze tracking device, the hardware processor beingprogrammed to: obtain a transcription of one of more words spoken by theuser into text, based at least in part on the speech data from the audiosensing device; control the display to present the text to the user;determine, based at least on data received from the eye gaze trackingdevice, that the user has given a command to select a portion of thepresented text for editing; and perform an editing action on the portionof the presented text.
 48. The system of claim 47, wherein the hardwareprocessor is further programmed to determine that the user has given thecommand to select the given word for editing based on data from the eyegaze tracking device indicating that the user's gaze has lingered on theportion of the presented text presented by the display for at least athreshold period of time.
 49. The system of claim 47, further comprisinga user input device, wherein the hardware processor is furtherprogrammed to determine that the user has given the command to selectthe portion of the presented text for editing based on data from theuser input device and data from the eye gaze tracking device indicatingthat the user input device received user input while the user's gaze wasfocused on the portion of the presented text presented by the display.50. The system of claim 47, wherein the hardware processor is programmedto determine that the user has given the command to select the portionof the presented text for editing based on data from the audio sensingdevice and data from the eye gaze tracking device indicating that theaudio sensing device received a voice command while the user's gaze wasfocused on the portion of the presented text presented by the display.51. The system of claim 47, further comprising an imaging system thatimages at least one hand of the user, wherein the processor isconfigured to determine that the user has given the command to selectthe portion of the presented text for editing based on data from theimaging system and data from the eye gaze tracking device indicatingthat the user made a command gesture with their hand while the user'sgaze was focused on the portion of the presented text presented by thedisplay.
 52. The system of claim 47, wherein the hardware processor isfurther programmed to: control the display to present alternativetranscriptions of the portion of the presented text in response to thecommand to select the given word for editing.
 53. The system of claim47, wherein the hardware processor is further programmed to: determine,based on additional data received from the eye gaze tracking device,that the user has given a command to replace the portion of thepresented text with a selected alternative transcription; revise thetext to replace the portion of the presented text with the selectedalternative transcription; and control the display to present therevised text to the user.
 54. The system of claim 47, wherein thehardware processor is further programmed to produce a score associatedwith one or more words in the text, which indicates a likelihood thatsuch words are correctly transcribed.
 55. The system of claim 54,wherein the hardware processor is further programmed to cause thedisplay to emphasize the one or more words if the likelihood of correcttranscription is below a threshold level.
 56. A method comprising: undercontrol of a hardware processor: receiving spoken input from a user froma microphone; translating the spoken input into text including aplurality of words; causing a wearable display to present the text tothe user; based at least on data from a gaze tracking system, receivinga selection of a portion of the presented text in the displayed text;and providing the user with an opportunity to edit the portion of thepresented text.
 57. The method of claim 56, wherein receiving theselection of the portion of the presented text comprises one or more of:determining that the user's gaze was focused on the portion of thepresented text for at least a predetermined threshold period of time;determining that the user's gaze is focused on the portion of thepresented text while receiving a spoken predetermined command from theuser requesting an edit with the microphone; determining that the user'sgaze is focused on the portion of the presented text while receivingdata for an actuation of a user input device; or determining that theuser's gaze is focused on the portion of the presented text andsubstantially while receiving data from a gesture tracking systemindicating that the user made a predetermined command gesture requestingan edit.
 58. The method of claim 57, further comprising: based at leastone data from the gaze tracking system, receiving a selection of anadditional word in the displayed text; and providing the user with anopportunity to edit a phrase formed from the portion of the presentedtext or an additional portion of the text.
 59. The method of claim 57,wherein at least a portion of the text is emphasized on the displaywhere the portion is associated with a low confidence that a translationfrom the spoken input to the corresponding portion of the text iscorrect.
 60. A method comprising: receiving a multimodal inputcomprising: first user input from a hardware component of a wearabledevice, wherein the first user input is associated with a first mode ofuser input, and a second user input, wherein the second user input isassociated with a second mode of user input; identifying a multimodalinput command based on the first user input and the second user input,the multimodal input command comprising at least: a subject comprisingat least a portion of a text, and a command operation comprising aninteraction with the text, and executing the multimodal input command tocause a result of the user multimodal input to be displayed to a user.61. The method of claim 60, wherein the first mode of user inputcomprises a speech input received from an audio sensor of the wearabledevice, wherein the method further comprises transcribing the speechinput to identify at least one of the text, the subject, or the commandoperation.
 62. The method of claim 60, wherein the second mode of userinput comprises an input from at least one of: a user input device, agesture, or an eye gaze.
 63. The method of claim 60, wherein theinteraction with the text comprises at least one of: selecting, editing,or composing the text.
 64. The method of claim 60, wherein the subjectcomprises one or more of: a word, a phrase, or a sentence.
 65. Themethod of claim 60, wherein the subject comprises a sentence and thecommand operation comprises selecting the sentence for editing, and themethod further comprises: performing a first user interface operationcomprising bringing the sentence out of a body of text; processing thesentence to generate a sequence of tokens; displaying as the sequence oftokens as primary results wherein the primary results comprise thesentence as transcribed from the user's speech; further displayingsecondary results, wherein the secondary results comprise alternativewords to tokens in the sequence; receiving another multimodal inputcomprising a third mode of input and a fourth mode of input for editingthe sequence on a word by word basis; and inserting the edited sequenceback to the body of text in response to an indication that the editingof the sequence has been completed.